feat(envs): add RoboCasa composite-task benchmark integration

Integrates 5 selected RoboCasa kitchen tasks (3 short + 2 long) as a LeRobot benchmark environment, following the same pattern as Libero. Selected tasks: Short: PickPlaceCounterToCabinet, PrepareToast, CoffeeSetupMug Long: PrepareCoffee, RestockPantry Changes: - envs/robocasa.py: RoboCasaEnv wrapper with flat 12D Box action space, 3-camera pixel obs, and 16D proprioceptive state - envs/configs.py: RoboCasaEnv config with features_map - envs/factory.py: wire robocasa into make_env + make_env_pre_post_processors - processor/env_processor.py: RoboCasaProcessorStep for obs key remapping - tests/test_robocasa_env.py: full test suite (auto-skips if assets missing) Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
chore(dependencies): Bump lerobot to 0.5.1 (#3118 )
2026-05-11 14:49:43 +00:00 · 2026-03-09 17:08:32 +01:00 · 2026-03-09 12:43:32 +01:00 · 2026-03-09 11:34:52 +01:00 · 2026-03-09 11:18:05 +01:00 · 2026-03-08 14:02:33 +01:00
55 changed files with 2637 additions and 1158 deletions
@@ -91,6 +91,7 @@ jobs:
        run: uv sync --extra "test"

      - name: Login to Hugging Face
+        if: env.HF_USER_TOKEN != ''
        run: |
          uv run hf auth login --token "$HF_USER_TOKEN" --add-to-git-credential
          uv run hf auth whoami
@@ -89,6 +89,7 @@ jobs:
        run: uv sync --extra all # TODO(Steven): Make flash-attn optional

      - name: Login to Hugging Face
+        if: env.HF_USER_TOKEN != ''
        run: |
          uv run hf auth login --token "$HF_USER_TOKEN" --add-to-git-credential
          uv run hf auth whoami
@@ -181,6 +182,7 @@ jobs:
        working-directory: /lerobot
    steps:
      - name: Login to Hugging Face
+        if: env.HF_USER_TOKEN != ''
        run: |
          hf auth login --token "$HF_USER_TOKEN" --add-to-git-credential
          hf auth whoami
@@ -132,6 +132,7 @@ jobs:
        working-directory: /lerobot
    steps:
      - name: Login to Hugging Face
+        if: env.HF_USER_TOKEN != ''
        run: |
          hf auth login --token "$HF_USER_TOKEN" --add-to-git-credential
          hf auth whoami
@@ -164,6 +165,7 @@ jobs:
        working-directory: /lerobot
    steps:
      - name: Login to Hugging Face
+        if: env.HF_USER_TOKEN != ''
        run: |
          hf auth login --token "$HF_USER_TOKEN" --add-to-git-credential
          hf auth whoami
@@ -197,6 +199,7 @@ jobs:
        working-directory: /lerobot
    steps:
      - name: Login to Hugging Face
+        if: env.HF_USER_TOKEN != ''
        run: |
          hf auth login --token "$HF_USER_TOKEN" --add-to-git-credential
          hf auth whoami
@@ -83,14 +83,6 @@ jobs:
            exit 1
          fi

-      - name: Remove Tags with Git dependencies
-        # TODO(Steven): Temporary patch to remove pi from PyPi 0.4.0 release due to its reliance on git dependencies.
-        run: |
-          echo "::info:: Checking for Git dependencies to remove from pyproject.toml..."
-          grep -E '@ git\+https|lerobot\[pi\]' pyproject.toml | sed 's/^/::warning:: Removing line: /' || true
-          sed -E -i '/@ git\+https|lerobot\[pi\]/d' pyproject.toml
-          echo "::info:: Git dependencies removed. Proceeding with build."
-
      - name: Install build dependencies
        run: python -m pip install build

@@ -81,6 +81,7 @@ jobs:
      - name: Install lerobot with all extras
        run: uv sync --extra all # TODO(Steven): Make flash-attn optional
      - name: Login to Hugging Face
+        if: env.HF_USER_TOKEN != ''
        run: |
          uv run hf auth login --token "$HF_USER_TOKEN" --add-to-git-credential
          uv run hf auth whoami
@@ -154,6 +155,7 @@ jobs:
        working-directory: /lerobot
    steps:
      - name: Login to Hugging Face
+        if: env.HF_USER_TOKEN != ''
        run: |
          hf auth login --token "$HF_USER_TOKEN" --add-to-git-credential
          hf auth whoami
@@ -135,7 +135,7 @@ Learn how to implement your own simulation environment or benchmark and distribu

 ## Citation

-If you use LeRobot in your research, please cite:
+If you use LeRobot in your project, please cite the GitHub repository to acknowledge the ongoing development and contributors:

 ```bibtex
@misc{cadene2024lerobot,
@@ -146,6 +146,23 @@ If you use LeRobot in your research, please cite:
 }
 ```

+If you are referencing our research or the academic paper, please also cite our ICLR publication:
+
+<details>
+<summary><b>ICLR 2026 Paper</b></summary>
+
+```bibtex
+@inproceedings{cadenelerobot,
+  title={LeRobot: An Open-Source Library for End-to-End Robot Learning},
+  author={Cadene, Remi and Alibert, Simon and Capuano, Francesco and Aractingi, Michel and Zouitine, Adil and Kooijmans, Pepijn and Choghari, Jade and Russi, Martino and Pascal, Caroline and Palma, Steven and Shukor, Mustafa and Moss, Jess and Soare, Alexander and Aubakirova, Dana and Lhoest, Quentin and Gallou\'edec, Quentin and Wolf, Thomas},
+  booktitle={The Fourteenth International Conference on Learning Representations},
+  year={2026},
+  url={https://arxiv.org/abs/2602.22818}
+}
+```
+
+</details>
+
 ## Contribute

 We welcome contributions from everyone in the community! To get started, please read our [CONTRIBUTING.md](./CONTRIBUTING.md) guide. Whether you're adding a new feature, improving documentation, or fixing a bug, your help and feedback are invaluable. We're incredibly excited about the future of open-source robotics and can't wait to work with you on what's next—thank you for your support!
@@ -1,8 +1,8 @@
 # Installation

-This guide uses conda (via miniforge) to manage environments. If you prefer another environment manager (e.g. `uv`, `venv`), ensure you have Python >=3.12 and ffmpeg installed with the `libsvtav1` encoder, then skip ahead to [Install LeRobot](#step-3-install-lerobot-).
+This guide uses `conda` (via miniforge) to manage environments (recommended). If you prefer another environment manager (e.g. `uv`, `venv`), ensure you have Python >=3.12 and `ffmpeg` installed with the `libsvtav1` encoder, then skip ahead to [Environment Setup](#step-2-environment-setup).

-## Step 1: Install [`miniforge`](https://conda-forge.org/download/)
+## Step 1 (`conda` only): Install [`miniforge`](https://conda-forge.org/download/)

 ```bash
 wget "https://github.com/conda-forge/miniforge/releases/latest/download/Miniforge3-$(uname)-$(uname -m).sh"
@@ -11,22 +11,47 @@ bash Miniforge3-$(uname)-$(uname -m).sh

 ## Step 2: Environment Setup

-Create a virtual environment with Python 3.12, using conda:
+Create a virtual environment with Python 3.12:

+<!-- prettier-ignore-start -->
+<hfoptions id="create_venv">
+<hfoption id="conda">
 ```bash
 conda create -y -n lerobot python=3.12
 ```
-
-Then activate your conda environment, you have to do this each time you open a shell to use lerobot:
-
+</hfoption>
+<hfoption id="uv">
 ```bash
-conda activate lerobot
+uv python install 3.12
+uv venv --python 3.12
 ```
+</hfoption>
+</hfoptions>
+<!-- prettier-ignore-end -->
+
+Then activate your virtual environment, you have to do this each time you open a shell to use lerobot:
+
+<!-- prettier-ignore-start -->
+<hfoptions id="activate_venv">
+<hfoption id="conda">```bash
+conda activate lerobot
+```</hfoption>
+<hfoption id="uv">
+```bash
+# Linux/macOSsource
+source .venv/bin/activate
+# Windows PowerShell
+source .venv\Scripts\Activate.ps1
+```
+</hfoption>
+</hfoptions>
+<!-- prettier-ignore-end -->

 When using `conda`, install `ffmpeg` in your environment:

 ```bash
 conda install ffmpeg -c conda-forge
+ffmpeg -version  # ffmpeg 8.X is not yet supported !
 ```

 > [!TIP]
@@ -47,6 +72,9 @@ conda install ffmpeg -c conda-forge
 > conda install evdev -c conda-forge
 > ```

+> [!IMPORTANT]
+> If you are using `uv` you will have to install `ffmpeg` system-wide (outside of the virtual environment). You rely on `uv` and `torchcodec` ability to dynamically link to the system `ffmpeg`.
+
 ## Step 3: Install LeRobot 🤗

 ### From Source
@@ -60,23 +88,45 @@ cd lerobot

 Then, install the library in editable mode. This is useful if you plan to contribute to the code.

+<!-- prettier-ignore-start -->
+<hfoptions id="install_lerobot_src">
+<hfoption id="conda">
 ```bash
 pip install -e .
 ```
+</hfoption>
+<hfoption id="uv">
+```bash
+uv pip install -e .
+```
+</hfoption>
+</hfoptions>
+<!-- prettier-ignore-end -->

 ### Installation from PyPI

 **Core Library:**
 Install the base package with:

+<!-- prettier-ignore-start -->
+<hfoptions id="install_lerobot_pypi">
+<hfoption id="conda">
 ```bash
 pip install lerobot
 ```
+</hfoption>
+<hfoption id="uv">
+```bash
+uv pip install lerobot
+```
+</hfoption>
+</hfoptions>
+<!-- prettier-ignore-end -->

 _This installs only the default dependencies._

 **Extra Features:**
-To install additional functionality, use one of the following:
+To install additional functionality, use one of the following (If you are using `uv`, replace `pip install` with `uv pip install` in the commands below.):

 ```bash
 pip install 'lerobot[all]'          # All available features
@@ -90,13 +140,10 @@ _Replace `[...]` with your desired features._
 For a full list of optional dependencies, see:
 https://pypi.org/project/lerobot/

-> [!NOTE]
-> For lerobot 0.4.0, if you want to install pi, you will have to do: `pip install "lerobot[pi]@git+https://github.com/huggingface/lerobot.git"`
-
 ### Troubleshooting

 If you encounter build errors, you may need to install additional dependencies: `cmake`, `build-essential`, and `ffmpeg libs`.
-To install these for linux run:
+To install these for Linux run:

 ```bash
 sudo apt-get install cmake build-essential python3-dev pkg-config libavformat-dev libavcodec-dev libavdevice-dev libavutil-dev libswscale-dev libswresample-dev libavfilter-dev
@@ -106,7 +153,7 @@ For other systems, see: [Compiling PyAV](https://pyav.org/docs/develop/overview/

 ## Optional dependencies

-LeRobot provides optional extras for specific functionalities. Multiple extras can be combined (e.g., `.[aloha,feetech]`). For all available extras, refer to `pyproject.toml`.
+LeRobot provides optional extras for specific functionalities. Multiple extras can be combined (e.g., `.[aloha,feetech]`). For all available extras, refer to `pyproject.toml`. If you are using `uv`, replace `pip install` with `uv pip install` in the commands below.

 ### Simulations

@@ -34,11 +34,6 @@ As described by Physical Intelligence, while AI has achieved remarkable success
   pip install -e ".[pi]"
   ```

-   > [!NOTE]
-   > For lerobot 0.4.0, if you want to install pi tag, you will have to do: `pip install "lerobot[pi]@git+https://github.com/huggingface/lerobot.git"`.
-   >
-   > This will be solved in the next patch release
-
 ## Training Data and Capabilities

 π₀ is trained on the largest robot interaction dataset to date, combining three key data sources:
@@ -36,11 +36,6 @@ This diverse training mixture creates a "curriculum" that enables generalization
   pip install -e ".[pi]"
   ```

-   > [!NOTE]
-   > For lerobot 0.4.0, if you want to install pi tag, you will have to do: `pip install "lerobot[pi]@git+https://github.com/huggingface/lerobot.git"`.
-   >
-   > This will be solved in the next patch release
-
 ## Usage

 To use π₀.₅ in your LeRobot configuration, specify the policy type as:
@@ -43,11 +43,6 @@ This approach can transform **any existing VLM** into a VLA by training it to pr
   pip install -e ".[pi]"
   ```

-   > [!NOTE]
-   > For lerobot 0.4.0, if you want to install the pi tag, you will have to do: `pip install "lerobot[pi]@git+https://github.com/huggingface/lerobot.git"`.
-   >
-   > This will be solved in the next patch release
-
 ## Training a Custom FAST Tokenizer

 You have two options for the FAST tokenizer:
@@ -1,23 +1,49 @@
 # Unitree G1

-This guide covers the complete setup process for the Unitree G1 humanoid, from initial connection to running gr00t_wbc locomotion.
+<img
+  src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/lerobot/unitree_thumbnail.jpg"
+  alt="Unitree G1 locomanipulation demo"
+  style={{ width: "100%" }}
+/>

-## About
-
-We support both 29 and 23 DOF G1 EDU version. We introduce:
-
- **`unitree g1` robot class, handling low level read/write from/to the humanoid**
- **ZMQ socket bridge** for remote communication and camera streaming, allowing for remote policy deployment over wlan, eth or directly on the robot
- **Locomotion policies** from NVIDIA gr00t and Amazon FAR Holosoma
- **Simulation mode** for testing policies without the physical robot in mujoco
+The Unitree G1 humanoid is now supported in LeRobot! You can teleoperate, train locomanipulation policies, test in sim, and more. Both 29 and 23 DoF variants are supported.

 ---

-## Connection guide
+## Part 1: Getting Started

-### Step 1: Configure Ethernet Interface
+### Install LeRobot on Your Machine

-Set a static IP on the same subnet as the robot:
+```bash
+conda create -y -n lerobot python=3.12
+conda activate lerobot
+git clone https://github.com/unitreerobotics/unitree_sdk2_python.git
+cd unitree_sdk2_python && pip install -e .
+git clone https://github.com/huggingface/lerobot.git
+cd lerobot
+pip install -e '.[unitree_g1]'
+```
+
+### Test the Installation (Simulation)
+
+```bash
+lerobot-teleoperate \
+  --robot.type=unitree_g1 \
+  --robot.is_simulation=true \
+  --teleop.type=unitree_g1 \
+  --teleop.id=wbc_unitree \
+  --robot.cameras='{"global_view": {"type": "zmq", "server_address": "localhost", "port": 5555, "camera_name": "head_camera", "width": 640, "height": 480, "fps": 30}}' \
+  --display_data=true
+```
+
+This will launch a [MuJoCo sim instance](https://huggingface.co/lerobot/unitree-g1-mujoco/tree/main) for the G1.
+
+- Press `9` to release the robot
+- Press `7` / `8` to increase / decrease waist height
+
+### Connect to the Robot
+
+The G1's Ethernet IP is fixed at `192.168.123.164`. Your machine must have a static IP on the same subnet: `192.168.123.x` where `x ≠ 164`.

 ```bash
 # Replace 'enp131s0' with your ethernet interface name (check with `ip a`)
@@ -26,272 +52,200 @@ sudo ip addr add 192.168.123.200/24 dev enp131s0
 sudo ip link set enp131s0 up
 ```

-**Note**: The G1's Ethernet IP is fixed at `192.168.123.164`. Your computer must use `192.168.123.x` with x ≠ 164.
-
-### Step 2: SSH into the Robot
+### SSH into the Robot

 ```bash
 ssh unitree@192.168.123.164
 # Password: 123
 ```

-You should now be connected to the G1's Orin.
+### Install LeRobot on the G1
+
+From the robot:
+
+```bash
+conda create -y -n lerobot python=3.12
+conda activate lerobot
+git clone https://github.com/unitreerobotics/unitree_sdk2_python.git
+cd unitree_sdk2_python && pip install -e .
+git clone https://github.com/huggingface/lerobot.git
+cd lerobot
+pip install -e '.[unitree_g1]'
+```
+
+> **Note:** The Unitree SDK requires CycloneDDS v0.10.2. See the [Unitree SDK docs](https://github.com/unitreerobotics/unitree_sdk2_python) for details.

 ---

 ## Part 2: Enable WiFi on the Robot

-Wlan0 is disabled by default on the G1. To enable it:
-
-### Step 1: Enable WiFi Hardware
+Wi-Fi connectivity is blocked by default on the G1. To activate:

 ```bash
-sudo rfkill unblock wifi
 sudo rfkill unblock all
-
-# Bring up wlan0
 sudo ip link set wlan0 up
-
-# Enable NetworkManager control of wlan0
 sudo nmcli radio wifi on
 sudo nmcli device set wlan0 managed yes
 sudo systemctl restart NetworkManager
 ```

-### Step 2: Enable Internet Forwarding
-
-**On your laptop:**
+**On your laptop** (share internet via Ethernet):

 ```bash
-# Enable IP forwarding
 sudo sysctl -w net.ipv4.ip_forward=1

-# Set up NAT (replace wlp132s0f0 with your WiFi interface)
+# Replace wlp132s0f0 with your WiFi interface name
 sudo iptables -t nat -A POSTROUTING -o wlp132s0f0 -s 192.168.123.0/24 -j MASQUERADE
 sudo iptables -A FORWARD -i wlp132s0f0 -o enp131s0 -m state --state RELATED,ESTABLISHED -j ACCEPT
 sudo iptables -A FORWARD -i enp131s0 -o wlp132s0f0 -j ACCEPT
 ```

-**On the G1:**
+**On the G1** (set default route through your laptop):

 ```bash
-# Add laptop as default gateway
 sudo ip route del default 2>/dev/null || true
 sudo ip route add default via 192.168.123.200 dev eth0
 echo "nameserver 8.8.8.8" | sudo tee /etc/resolv.conf

-# Test connection
+# Verify
 ping -c 3 8.8.8.8
 ```

-### Step 3: Connect to WiFi Network
+**Connect to a WiFi network:**

 ```bash
-# List available networks
 nmcli device wifi list

-# Connect to your WiFi (example)
 sudo nmcli connection add type wifi ifname wlan0 con-name "YourNetwork" ssid "YourNetwork"
 sudo nmcli connection modify "YourNetwork" wifi-sec.key-mgmt wpa-psk
 sudo nmcli connection modify "YourNetwork" wifi-sec.psk "YourPassword"
 sudo nmcli connection modify "YourNetwork" connection.autoconnect yes
 sudo nmcli connection up "YourNetwork"

-# Check WiFi IP address
 ip a show wlan0
 ```

-### Step 4: SSH Over WiFi
-
-Once connected to WiFi, note the robot's IP address and disconnect the Ethernet cable. You can now SSH over WiFi:
+You can now SSH over WiFi:

 ```bash
-ssh unitree@<YOUR_ROBOT_IP>
+ssh unitree@<ROBOT_WIFI_IP>
 # Password: 123
 ```

-Replace `<YOUR_ROBOT_IP>` with your robot's actual WiFi IP address.
-
 ---

-## Part 3: Robot Server Setup
+## Part 3: Teleoperation & Locomotion

-### Step 1: Install LeRobot on the Orin
-
-SSH into the robot and install LeRobot:
-
-```bash
-ssh unitree@<YOUR_ROBOT_IP>
-
-conda create -y -n lerobot python=3.12
-conda activate lerobot
-git clone https://github.com/huggingface/lerobot.git
-cd lerobot
-pip install -e '.[unitree_g1]'
-git clone https://github.com/unitreerobotics/unitree_sdk2_python.git
-cd unitree_sdk2_python  && pip install -e .
-```
-
-**Note**: The Unitree SDK requires CycloneDDS v0.10.2 to be installed. See the [Unitree SDK documentation](https://github.com/unitreerobotics/unitree_sdk2_python) for details.
-
-### Step 2: Run the Robot Server
+### Run the Robot Server

 On the robot:

 ```bash
-python src/lerobot/robots/unitree_g1/run_g1_server.py
+python src/lerobot/robots/unitree_g1/run_g1_server.py --camera
 ```

-**Important**: Keep this terminal running. The server must be active for remote control.
+### Run the Locomotion Policy
+
+```bash
+lerobot-teleoperate \
+  --robot.type=unitree_g1 \
+  --robot.is_simulation=false \
+  --robot.robot_ip=<ROBOT_IP> \
+  --teleop.type=unitree_g1 \
+  --teleop.id=wbc_unitree \
+  --robot.cameras='{"global_view": {"type": "zmq", "server_address": "<ROBOT_IP>", "port": 5555, "camera_name": "head_camera", "width": 640, "height": 480, "fps": 30}}' \
+  --display_data=true \
+  --robot.controller=HolosomaLocomotionController
+```
+
+We support both [HolosomaLocomotionController](https://github.com/amazon-far/holosoma) and [GrootLocomotionController](https://github.com/NVlabs/GR00T-WholeBodyControl).

 ---

-## Part 4: Controlling the robot
+## Part 4: Loco-Manipulation with the Homunculus Exoskeleton

-With the robot server running, you can now control the robot remotely. Let's launch a locomotion policy
+We provide a loco-manipulation solution via the Homunculus Exoskeleton — an open-source 7 DoF exoskeleton for whole-body control. Assembly instructions [here](https://github.com/nepyope/hmc_exo).

-### Step 1: Install LeRobot on your machine
-
-```bash
-conda create -y -n lerobot python=3.12
-conda activate lerobot
-git clone https://github.com/huggingface/lerobot.git
-cd lerobot
-pip install -e '.[unitree_g1]'
-git clone https://github.com/unitreerobotics/unitree_sdk2_python.git
-cd unitree_sdk2_python  && pip install -e .
-```
-
-### Step 2: Update Robot IP in Config
-
-Edit the config file to match your robot's WiFi IP:
-
-```python
-# In src/lerobot/robots/unitree_g1/config_unitree_g1.py
-robot_ip: str = "<YOUR_ROBOT_IP>"  # Replace with your robot's WiFi IP.
-```
-
-### Step 3: Run the Locomotion Policy
-
-```bash
-# Run GR00T locomotion controller
-python examples/unitree_g1/gr00t_locomotion.py --repo-id "nepyope/GR00T-WholeBodyControl_g1"
-
-# Run Holosoma locomotion controller
-python examples/unitree_g1/holosoma_locomotion.py
-
-```
-
-Press `Ctrl+C` to stop the policy.
-
---
-
-## Running in Simulation Mode (MuJoCo)
-
-You can test policies before deploying on the physical robot using MuJoCo simulation. Set `is_simulation=True` in config or pass `--robot.is_simulation=true` via CLI.
-
-### Calibrate Exoskeleton Teleoperator
+### Calibrate

 ```bash
 lerobot-calibrate \
-    --teleop.type=unitree_g1 \
-    --teleop.left_arm_config.port=/dev/ttyACM1 \
-    --teleop.right_arm_config.port=/dev/ttyACM0 \
-    --teleop.id=exo
+  --teleop.type=unitree_g1 \
+  --teleop.left_arm_config.port=/dev/ttyACM1 \
+  --teleop.right_arm_config.port=/dev/ttyACM0 \
+  --teleop.id=exo
 ```

-### Teleoperate in Simulation
+During calibration move each joint through its entire range. After fitting, move the joint in a neutral position and press `n` to advance.

-```bash
-lerobot-teleoperate \
-    --robot.type=unitree_g1 \
-    --robot.is_simulation=true \
-    --teleop.type=unitree_g1 \
-    --teleop.left_arm_config.port=/dev/ttyACM1 \
-    --teleop.right_arm_config.port=/dev/ttyACM0 \
-    --teleop.id=exo \
-    --fps=100
-```
-
-### Record Dataset in Simulation
+### Record a Dataset

 ```bash
 lerobot-record \
-    --robot.type=unitree_g1 \
-    --robot.is_simulation=true \
-    --robot.cameras='{"global_view": {"type": "zmq", "server_address": "localhost", "port": 5555, "camera_name": "head_camera", "width": 640, "height": 480, "fps": 30}}' \
-    --teleop.type=unitree_g1 \
-    --teleop.left_arm_config.port=/dev/ttyACM1 \
-    --teleop.right_arm_config.port=/dev/ttyACM0 \
-    --teleop.id=exo \
-    --dataset.repo_id=your-username/dataset-name \
-    --dataset.single_task="Test" \
-    --dataset.num_episodes=2 \
-    --dataset.episode_time_s=5 \
-    --dataset.reset_time_s=5 \
-    --dataset.push_to_hub=true \
-    --dataset.streaming_encoding=true \
-    # --dataset.vcodec=auto \
-    --dataset.encoder_threads=2
+  --robot.type=unitree_g1 \
+  --robot.is_simulation=true \
+  --robot.cameras='{"global_view": {"type": "zmq", "server_address": "localhost", "port": 5555, "camera_name": "head_camera", "width": 640, "height": 480, "fps": 30}}' \
+  --teleop.type=unitree_g1 \
+  --teleop.left_arm_config.port=/dev/ttyACM1 \
+  --teleop.right_arm_config.port=/dev/ttyACM0 \
+  --teleop.id=exo \
+  --dataset.repo_id=your-username/dataset-name \
+  --dataset.single_task="Test" \
+  --dataset.num_episodes=2 \
+  --dataset.episode_time_s=5 \
+  --dataset.reset_time_s=5 \
+  --dataset.push_to_hub=true \
+  --dataset.streaming_encoding=true \
+  --dataset.encoder_threads=2
 ```

-Example simulation dataset: [nepyope/teleop_test_sim](https://huggingface.co/datasets/nepyope/teleop_test_sim)
+> **Note:** Omit `--teleop.left_arm_config.port` and `--teleop.right_arm_config.port` if you're only using the joystick.
+
+Example dataset: [nepyope/unitree_box_move_blue_full](https://huggingface.co/datasets/nepyope/unitree_box_move_blue_full)

 ---

-## Running on Real Robot
+## Part 5: Training & Inference

-Once the robot server is running on the G1 (see Part 3), you can teleoperate and record on the real robot.
-
-### Start the Camera Server
-
-On the robot, start the ZMQ image server:
+### Train

 ```bash
-python src/lerobot/cameras/zmq/image_server.py
+python src/lerobot/scripts/lerobot_train.py \
+  --dataset.repo_id=your-username/dataset-name  \
+  --policy.type=pi05 \
+  --output_dir=./outputs/pi05_training \
+  --job_name=pi05_training \
+  --policy.repo_id=your-username/your-repo-id \
+  --policy.pretrained_path=lerobot/pi05_base \
+  --policy.compile_model=true \
+  --policy.gradient_checkpointing=true \
+  --wandb.enable=true \
+  --policy.dtype=bfloat16 \
+  --policy.freeze_vision_encoder=false \
+  --policy.train_expert_only=false \
+  --steps=3000 \
+  --policy.device=cuda \
+  --batch_size=32
 ```

-Keep this running in a separate terminal for camera streaming during recording.
+### Inference with RTC

-### Teleoperate Real Robot
+Once trained, we recommend deploying policies using inference-time RTC:

 ```bash
-lerobot-teleoperate \
-    --robot.type=unitree_g1 \
-    --robot.is_simulation=false \
-    --teleop.type=unitree_g1 \
-    --teleop.left_arm_config.port=/dev/ttyACM1 \
-    --teleop.right_arm_config.port=/dev/ttyACM0 \
-    --teleop.id=exo \
-    --fps=100
+python examples/rtc/eval_with_real_robot.py \
+  --policy.path=your-username/your-repo-id \
+  --policy.device=cuda \
+  --robot.type=unitree_g1 \
+  --robot.is_simulation=false \
+  --robot.controller=HolosomaLocomotionController \
+  --robot.cameras='{"global_view": {"type": "zmq", "server_address": "<ROBOT_IP>", "port": 5555, "camera_name": "head_camera", "width": 640, "height": 480, "fps": 30}}' \
+  --task="task_description" \
+  --duration=1000 \
+  --fps=30 \
+  --rtc.enabled=true
 ```

-### Record Dataset on Real Robot
-
-```bash
-lerobot-record \
-    --robot.type=unitree_g1 \
-    --robot.is_simulation=false \
-    --robot.cameras='{"global_view": {"type": "zmq", "server_address": "172.18.129.215", "port": 5555, "camera_name": "head_camera", "width": 640, "height": 480, "fps": 30}}' \
-    --teleop.type=unitree_g1 \
-    --teleop.left_arm_config.port=/dev/ttyACM1 \
-    --teleop.right_arm_config.port=/dev/ttyACM0 \
-    --teleop.id=exo \
-    --dataset.repo_id=your-username/dataset-name \
-    --dataset.single_task="Test" \
-    --dataset.num_episodes=2 \
-    --dataset.episode_time_s=5 \
-    --dataset.reset_time_s=5 \
-    --dataset.push_to_hub=true \
-    --dataset.streaming_encoding=true \
-    # --dataset.vcodec=auto \
-    --dataset.encoder_threads=2
-```
-
-**Note**: Update `server_address` to match your robot's camera server IP.
-
-Example real robot dataset: [nepyope/teleop_test_real](https://huggingface.co/datasets/nepyope/teleop_test_real)
-
 ---

 ## Additional Resources
@@ -300,8 +254,8 @@ Example real robot dataset: [nepyope/teleop_test_real](https://huggingface.co/da
 - [GR00T-WholeBodyControl](https://github.com/NVlabs/GR00T-WholeBodyControl)
 - [Holosoma](https://github.com/amazon-far/holosoma)
 - [LeRobot Documentation](https://github.com/huggingface/lerobot)
- [Unitree_IL_Lerobot](https://github.com/unitreerobotics/unitree_IL_lerobot)
+- [Unitree IL LeRobot](https://github.com/unitreerobotics/unitree_IL_lerobot)

 ---

-_Last updated: December 2025_
+_Last updated: March 2026_
@@ -78,6 +78,7 @@ from torch import Tensor

 from lerobot.cameras.opencv.configuration_opencv import OpenCVCameraConfig  # noqa: F401
 from lerobot.cameras.realsense.configuration_realsense import RealSenseCameraConfig  # noqa: F401
+from lerobot.cameras.zmq.configuration_zmq import ZMQCameraConfig  # noqa: F401
 from lerobot.configs import parser
 from lerobot.configs.policies import PreTrainedConfig
 from lerobot.configs.types import RTCAttentionSchedule
@@ -97,6 +98,7 @@ from lerobot.robots import (  # noqa: F401
    bi_so_follower,
    koch_follower,
    so_follower,
+    unitree_g1,
 )
 from lerobot.robots.utils import make_robot_from_config
 from lerobot.utils.constants import OBS_IMAGES
@@ -25,7 +25,7 @@ discord = "https://discord.gg/s3KuuzsPFb"

 [project]
 name = "lerobot"
-version = "0.4.5"
+version = "0.5.1"
 description = "🤗 LeRobot: State-of-the-art Machine Learning for Real-World Robotics in Pytorch"
 dynamic = ["readme"]
 license = { text = "Apache-2.0" }
@@ -66,7 +66,7 @@ dependencies = [
    "accelerate>=1.10.0,<2.0.0",

    # Core dependencies
-    "numpy>=2.0.0,<2.3.0", # TODO: upper bound imposed by opencv-python-headless
+    "numpy>=2.0.0,<2.3.0", # NOTE: Explicitly listing numpy helps the resolver converge faster. Upper bound imposed by opencv-python-headless.
    "setuptools>=71.0.0,<81.0.0",
    "cmake>=3.29.0.1,<4.2.0",
    "packaging>=24.2,<26.0",
@@ -105,7 +105,7 @@ can-dep = ["python-can>=4.2.0,<5.0.0"]
 peft-dep = ["peft>=0.18.0,<1.0.0"]
 scipy-dep = ["scipy>=1.14.0,<2.0.0"]
 qwen-vl-utils-dep = ["qwen-vl-utils>=0.0.11,<0.1.0"]
-matplotlib-dep = ["matplotlib>=3.10.3,<4.0.0", "contourpy>=1.3.0,<2.0.0"]
+matplotlib-dep = ["matplotlib>=3.10.3,<4.0.0", "contourpy>=1.3.0,<2.0.0"] # NOTE: Explicitly listing contourpy helps the resolver converge faster.

 # Motors
 feetech = ["feetech-servo-sdk>=1.0.0,<2.0.0"]
@@ -119,18 +119,20 @@ gamepad = ["lerobot[pygame-dep]", "hidapi>=0.14.0,<0.15.0"]
 hopejr = ["lerobot[feetech]", "lerobot[pygame-dep]"]
 lekiwi = ["lerobot[feetech]", "pyzmq>=26.2.1,<28.0.0"]
 unitree_g1 = [
+    "unitree-sdk2==1.0.1",
    "pyzmq>=26.2.1,<28.0.0",
    "onnxruntime>=1.16.0,<2.0.0",
    "pin>=3.0.0,<4.0.0",
    "meshcat>=0.3.0,<0.4.0",
    "lerobot[matplotlib-dep]",
+    "lerobot[pygame-dep]",
    "casadi>=3.6.0,<4.0.0",
 ]
 reachy2 = ["reachy2_sdk>=1.0.15,<1.1.0"]
 kinematics = ["lerobot[placo-dep]"]
 intelrealsense = [
    "pyrealsense2>=2.55.1.6486,<2.57.0 ; sys_platform != 'darwin'",
-    "pyrealsense2-macosx>=2.54,<2.55.0 ; sys_platform == 'darwin'",
+    "pyrealsense2-macosx>=2.54,<2.57.0 ; sys_platform == 'darwin'",
 ]
 phone = ["hebi-py>=2.8.0,<2.12.0", "teleop>=0.1.0,<0.2.0", "fastapi<1.0", "lerobot[scipy-dep]"]

@@ -169,6 +171,7 @@ test = ["pytest>=8.1.0,<9.0.0", "pytest-timeout>=2.4.0,<3.0.0", "pytest-cov>=5.0
 video_benchmark = ["scikit-image>=0.23.2,<0.26.0", "pandas>=2.2.2,<2.4.0"]

 # Simulation
+# NOTE: Explicitly listing scipy helps flatten the dependecy tree.
 aloha = ["gym-aloha>=0.1.2,<0.2.0", "lerobot[scipy-dep]"]
 pusht = ["gym-pusht>=0.1.5,<0.2.0", "pymunk>=6.6.0,<7.0.0"] # TODO: Fix pymunk version in gym-pusht instead
 libero = ["lerobot[transformers-dep]", "hf-libero>=0.1.3,<0.2.0; sys_platform == 'linux'", "lerobot[scipy-dep]"]
@@ -176,8 +179,8 @@ metaworld = ["metaworld==3.0.0", "lerobot[scipy-dep]"]

 # All
 all = [
-    # Resolver hint: scipy is pulled in transitively via lerobot[scipy-dep] through
-    # multiple extras below (aloha, metaworld, pi, wallx, phone). Listing it explicitly
+    # NOTE(resolver hint): scipy is pulled in transitively via lerobot[scipy-dep] through
+    # multiple extras (aloha, metaworld, pi, wallx, phone). Listing it explicitly
    # helps pip's resolver converge by constraining scipy early, before it encounters
    # the loose scipy requirements from transitive deps like dm-control and metaworld.
    "scipy>=1.14.0,<2.0.0",
@@ -205,6 +208,7 @@ all = [
    "lerobot[metaworld]",
    "lerobot[sarm]",
    "lerobot[peft]",
+    # "lerobot[unitree_g1]", TODO: Unitree requires specific installation instructions for unitree_sdk2
 ]

 [project.scripts]
@@ -1,76 +1,73 @@
 #
-# This file is autogenerated by pip-compile with Python 3.10
+# This file is autogenerated by pip-compile with Python 3.12
 # by the following command:
 #
 #    pip-compile --output-file=requirements-macos.txt requirements.in
 #
 -e .[all]
    # via -[all]
-absl-py==2.3.1
+absl-py==2.4.0
    # via
    #   dm-control
    #   dm-env
    #   dm-tree
    #   labmaze
    #   mujoco
-    #   tensorboard
-accelerate==1.11.0
+accelerate==1.13.0
    # via
    #   lerobot
    #   peft
 aiohappyeyeballs==2.6.1
    # via aiohttp
-aiohttp==3.13.1
+aiohttp==3.13.3
    # via fsspec
 aiosignal==1.4.0
    # via aiohttp
+annotated-doc==0.0.4
+    # via
+    #   fastapi
+    #   typer
 annotated-types==0.7.0
    # via pydantic
-antlr4-python3-runtime==4.9.3
-    # via
-    #   hydra-core
-    #   omegaconf
-anyio==4.11.0
+anyio==4.12.1
    # via
+    #   httpx
    #   starlette
    #   watchfiles
-asttokens==3.0.0
+asttokens==3.0.1
    # via stack-data
-async-timeout==5.0.1
-    # via aiohttp
 attrs==25.4.0
    # via
    #   aiohttp
    #   dm-tree
    #   jsonlines
-    #   jsonschema
-    #   referencing
    #   rerun-sdk
 av==15.1.0
-    # via lerobot
-bddl==1.0.1
-    # via libero
-certifi==2025.10.5
    # via
+    #   lerobot
+    #   qwen-vl-utils
+certifi==2026.2.25
+    # via
+    #   httpcore
+    #   httpx
    #   requests
    #   sentry-sdk
 cffi==2.0.0
    # via pymunk
-cfgv==3.4.0
+cfgv==3.5.0
    # via pre-commit
-charset-normalizer==3.4.4
+charset-normalizer==3.4.5
    # via requests
-click==8.3.0
+click==8.3.1
    # via
+    #   typer
    #   uvicorn
    #   wandb
-cloudpickle==3.1.1
-    # via
-    #   gymnasium
-    #   libero
-cmake==4.1.0
+cloudpickle==3.1.2
+    # via gymnasium
+cmake==4.1.3
    # via lerobot
-cmeel==0.57.3
+cmeel==0.59.0
    # via
    #   cmeel-assimp
    #   cmeel-boost
@@ -108,15 +105,17 @@ cmeel-zlib==1.3.1
    # via cmeel-assimp
 coal-library==3.0.1
    # via pin
-contourpy==1.3.2
-    # via matplotlib
-coverage[toml]==7.11.0
+contourpy==1.3.3
+    # via
+    #   lerobot
+    #   matplotlib
+coverage[toml]==7.13.4
    # via pytest-cov
 cycler==0.12.1
    # via matplotlib
-datasets==4.1.1
+datasets==4.6.1
    # via lerobot
-debugpy==1.8.17
+debugpy==1.8.20
    # via lerobot
 decorator==5.2.1
    # via ipython
@@ -130,7 +129,7 @@ dill==0.4.0
    #   multiprocess
 distlib==0.4.0
    # via virtualenv
-dm-control==1.0.34
+dm-control==1.0.37
    # via gym-aloha
 dm-env==1.6
    # via dm-control
@@ -138,69 +137,55 @@ dm-tree==0.1.9
    # via
    #   dm-control
    #   dm-env
-    #   lerobot
 docopt==0.6.2
    # via num2words
 draccus==0.10.0
    # via lerobot
 dynamixel-sdk==3.8.4
    # via lerobot
-easydict==1.13
-    # via libero
-egl-probe @ git+https://github.com/huggingface/egl_probe.git
-    # via
-    #   libero
-    #   robomimic
 eigenpy==3.10.3
    # via coal-library
-einops==0.8.1
-    # via
-    #   lerobot
-    #   libero
+einops==0.8.2
+    # via lerobot
 eiquadprog==1.2.9
    # via placo
-etils[epath,epy]==1.13.0
+etils[epath,epy]==1.14.0
    # via mujoco
-exceptiongroup==1.3.0
-    # via
-    #   anyio
-    #   ipython
-    #   pytest
 executing==2.2.1
    # via stack-data
+faker==34.0.2
+    # via lerobot
 farama-notifications==0.0.4
    # via gymnasium
-fastapi==0.119.1
-    # via teleop
-fastjsonschema==2.21.2
-    # via nbformat
+fastapi==0.135.1
+    # via
+    #   lerobot
+    #   teleop
 feetech-servo-sdk==1.0.0
    # via lerobot
-filelock==3.20.0
+filelock==3.25.0
    # via
    #   datasets
    #   diffusers
    #   huggingface-hub
+    #   python-discovery
    #   torch
-    #   transformers
    #   virtualenv
-fonttools==4.60.1
+fonttools==4.61.1
    # via matplotlib
 frozenlist==1.8.0
    # via
    #   aiohttp
    #   aiosignal
-fsspec[http]==2025.9.0
+fsspec[http]==2026.2.0
    # via
    #   datasets
    #   etils
    #   huggingface-hub
    #   torch
-future==1.0.0
-    # via libero
 gitdb==4.0.12
    # via gitpython
-gitpython==3.1.45
+gitpython==3.1.46
    # via wandb
 glfw==2.10.0
    # via
@@ -212,7 +197,6 @@ grpcio==1.73.1
    #   lerobot
    #   reachy2-sdk
    #   reachy2-sdk-api
-    #   tensorboard
 grpcio-tools==1.73.1
    # via
    #   lerobot
@@ -223,71 +207,67 @@ gym-hil==0.1.13
    # via lerobot
 gym-pusht==0.1.6
    # via lerobot
-gymnasium==1.2.1
+gymnasium==1.2.3
    # via
    #   gym-aloha
    #   gym-hil
    #   gym-pusht
    #   lerobot
-    #   libero
    #   metaworld
 h11==0.16.0
-    # via uvicorn
-h5py==3.15.1
-    # via robomimic
+    # via
+    #   httpcore
+    #   uvicorn
 hebi-py==2.11.0
    # via lerobot
-hf-transfer==0.1.9
-    # via huggingface-hub
-hf-xet==1.1.10
+hf-xet==1.3.2
    # via huggingface-hub
 hidapi==0.14.0.post4
    # via
    #   gym-hil
    #   lerobot
+httpcore==1.0.9
+    # via httpx
 httptools==0.7.1
    # via uvicorn
-huggingface-hub[cli,hf-transfer]==0.35.3
+httpx==0.28.1
+    # via
+    #   datasets
+    #   huggingface-hub
+huggingface-hub==1.6.0
    # via
    #   accelerate
    #   datasets
    #   diffusers
    #   lerobot
    #   peft
-    #   timm
    #   tokenizers
    #   transformers
-hydra-core==1.3.2
-    # via libero
-identify==2.6.15
+identify==2.6.17
    # via pre-commit
 idna==3.11
    # via
    #   anyio
+    #   httpx
    #   requests
    #   yarl
-imageio[ffmpeg]==2.37.0
+imageio[ffmpeg]==2.37.2
    # via
    #   gym-aloha
    #   gym-hil
    #   lerobot
    #   metaworld
-    #   robomimic
    #   scikit-image
 imageio-ffmpeg==0.6.0
-    # via
-    #   imageio
-    #   robomimic
-importlib-metadata==8.7.0
+    # via imageio
+importlib-metadata==8.7.1
    # via diffusers
-importlib-resources==6.5.2
-    # via etils
 iniconfig==2.3.0
    # via pytest
-inquirerpy==0.3.4
-    # via huggingface-hub
-ipython==8.37.0
+ipython==9.11.0
    # via meshcat
+ipython-pygments-lexers==1.1.1
+    # via ipython
 ischedule==1.2.7
    # via placo
 jedi==0.19.2
@@ -296,44 +276,24 @@ jinja2==3.1.6
    # via torch
 jsonlines==4.0.0
    # via lerobot
-jsonschema==4.25.1
-    # via nbformat
-jsonschema-specifications==2025.9.1
-    # via jsonschema
-jupyter-core==5.9.1
-    # via nbformat
-jupytext==1.18.1
-    # via bddl
 kiwisolver==1.4.9
    # via matplotlib
 labmaze==1.0.6
    # via dm-control
-lazy-loader==0.4
+lazy-loader==0.5
    # via scikit-image
-libero @ git+https://github.com/huggingface/lerobot-libero.git@main
-    # via lerobot
-llvmlite==0.45.1
-    # via numba
+librt==0.8.1
+    # via mypy
 lxml==6.0.2
    # via dm-control
-markdown==3.9
-    # via tensorboard
 markdown-it-py==4.0.0
-    # via
-    #   jupytext
-    #   mdit-py-plugins
+    # via rich
 markupsafe==3.0.3
-    # via
-    #   jinja2
-    #   werkzeug
-matplotlib==3.10.7
-    # via
-    #   lerobot
-    #   libero
+    # via jinja2
+matplotlib==3.10.8
+    # via lerobot
 matplotlib-inline==0.2.1
    # via ipython
-mdit-py-plugins==0.5.0
-    # via jupytext
 mdurl==0.1.2
    # via markdown-it-py
 mergedeep==1.3.4
@@ -346,41 +306,35 @@ mock-serial==0.0.1
    # via lerobot
 mpmath==1.3.0
    # via sympy
-mujoco==3.3.7
+mujoco==3.5.0
    # via
    #   dm-control
    #   gym-aloha
    #   gym-hil
-    #   libero
    #   metaworld
-    #   robosuite
-multidict==6.7.0
+multidict==6.7.1
    # via
    #   aiohttp
    #   yarl
-multiprocess==0.70.16
+multiprocess==0.70.18
    # via datasets
+mypy==1.19.1
+    # via lerobot
 mypy-extensions==1.1.0
-    # via typing-inspect
-nbformat==5.10.4
-    # via jupytext
-networkx==3.4.2
    # via
-    #   bddl
+    #   mypy
+    #   typing-inspect
+networkx==3.6.1
+    # via
    #   scikit-image
    #   torch
-ninja==1.13.0
-    # via lerobot
-nodeenv==1.9.1
+nodeenv==1.10.0
    # via pre-commit
 num2words==0.5.14
    # via lerobot
-numba==0.62.1
-    # via robosuite
 numpy==2.2.6
    # via
    #   accelerate
-    #   bddl
    #   cmeel-boost
    #   contourpy
    #   datasets
@@ -389,16 +343,14 @@ numpy==2.2.6
    #   dm-env
    #   dm-tree
    #   gymnasium
-    #   h5py
    #   hebi-py
    #   imageio
    #   labmaze
-    #   libero
+    #   lerobot
    #   matplotlib
    #   meshcat
    #   metaworld
    #   mujoco
-    #   numba
    #   opencv-python
    #   opencv-python-headless
    #   pandas
@@ -406,26 +358,18 @@ numpy==2.2.6
    #   pyquaternion
    #   reachy2-sdk
    #   rerun-sdk
-    #   robomimic
-    #   robosuite
    #   scikit-image
    #   scipy
    #   shapely
    #   teleop
-    #   tensorboard
-    #   tensorboardx
    #   tifffile
    #   torchvision
    #   transformers
    #   transforms3d
-omegaconf==2.3.0
-    # via hydra-core
-opencv-python==4.12.0.88
+opencv-python==4.13.0.92
    # via
    #   gym-pusht
-    #   libero
    #   reachy2-sdk
-    #   robosuite
 opencv-python-headless==4.12.0.88
    # via lerobot
 orderly-set==5.5.0
@@ -435,97 +379,87 @@ packaging==25.0
    #   accelerate
    #   datasets
    #   huggingface-hub
-    #   hydra-core
-    #   jupytext
    #   lazy-loader
    #   lerobot
    #   matplotlib
    #   peft
    #   pytest
+    #   qwen-vl-utils
    #   reachy2-sdk
    #   scikit-image
-    #   tensorboard
-    #   tensorboardx
    #   transformers
    #   wandb
 pandas==2.3.3
    # via
    #   datasets
    #   lerobot
-parso==0.8.5
+parso==0.8.6
    # via jedi
-peft==0.17.1
+pathspec==1.0.4
+    # via mypy
+peft==0.18.1
    # via lerobot
 pexpect==4.9.0
    # via ipython
-pfzy==0.3.4
-    # via inquirerpy
-pillow==12.0.0
+pillow==12.1.1
    # via
    #   diffusers
    #   imageio
-    #   lerobot
    #   matplotlib
    #   meshcat
+    #   qwen-vl-utils
    #   rerun-sdk
-    #   robosuite
    #   scikit-image
-    #   tensorboard
    #   torchvision
 pin==3.4.0
    # via placo
-placo==0.9.14
+placo==0.9.16
    # via lerobot
-platformdirs==4.5.0
+platformdirs==4.9.4
    # via
-    #   jupyter-core
+    #   python-discovery
    #   virtualenv
    #   wandb
 pluggy==1.6.0
    # via
    #   pytest
    #   pytest-cov
-pre-commit==4.3.0
+pre-commit==4.5.1
    # via lerobot
 prompt-toolkit==3.0.52
-    # via
-    #   inquirerpy
-    #   ipython
+    # via ipython
 propcache==0.4.1
    # via
    #   aiohttp
    #   yarl
-protobuf==6.31.0
+protobuf==6.31.1
    # via
    #   dm-control
    #   grpcio-tools
    #   lerobot
    #   reachy2-sdk
    #   reachy2-sdk-api
-    #   tensorboard
-    #   tensorboardx
    #   wandb
-psutil==7.1.1
+psutil==7.2.2
    # via
    #   accelerate
    #   imageio
    #   peft
-    #   robomimic
 ptyprocess==0.7.0
    # via pexpect
 pure-eval==0.2.3
    # via stack-data
-pyarrow==21.0.0
+pyarrow==23.0.1
    # via
    #   datasets
    #   rerun-sdk
-pycparser==2.23
+pycparser==3.0
    # via cffi
-pydantic==2.12.3
+pydantic==2.12.5
    # via
    #   fastapi
    #   wandb
-pydantic-core==2.41.4
+pydantic-core==2.41.5
    # via pydantic
 pygame==2.6.1
    # via
@@ -535,33 +469,35 @@ pygame==2.6.1
 pygments==2.19.2
    # via
    #   ipython
+    #   ipython-pygments-lexers
    #   pytest
+    #   rich
 pymunk==6.11.1
    # via
    #   gym-pusht
    #   lerobot
-pyngrok==7.4.1
+pyngrok==7.5.1
    # via meshcat
 pynput==1.8.1
    # via
    #   gym-hil
    #   lerobot
-pyobjc-core==12.0
+pyobjc-core==12.1
    # via
    #   pyobjc-framework-applicationservices
    #   pyobjc-framework-cocoa
    #   pyobjc-framework-coretext
    #   pyobjc-framework-quartz
-pyobjc-framework-applicationservices==12.0
+pyobjc-framework-applicationservices==12.1
    # via pynput
-pyobjc-framework-cocoa==12.0
+pyobjc-framework-cocoa==12.1
    # via
    #   pyobjc-framework-applicationservices
    #   pyobjc-framework-coretext
    #   pyobjc-framework-quartz
-pyobjc-framework-coretext==12.0
+pyobjc-framework-coretext==12.1
    # via pyobjc-framework-applicationservices
-pyobjc-framework-quartz==12.0
+pyobjc-framework-quartz==12.1
    # via
    #   pynput
    #   pyobjc-framework-applicationservices
@@ -570,13 +506,13 @@ pyopengl==3.1.10
    # via
    #   dm-control
    #   mujoco
-pyparsing==3.2.5
+pyparsing==3.3.2
    # via
    #   dm-control
    #   matplotlib
 pyquaternion==0.9.9
    # via reachy2-sdk
-pyrealsense2-macosx==2.54.2
+pyrealsense2-macosx==2.56.5
    # via lerobot
 pyserial==3.5
    # via
@@ -585,7 +521,6 @@ pyserial==3.5
    #   lerobot
 pytest==8.4.2
    # via
-    #   bddl
    #   lerobot
    #   pytest-cov
    #   pytest-timeout
@@ -596,11 +531,14 @@ pytest-timeout==2.4.0
    # via lerobot
 python-dateutil==2.9.0.post0
    # via
+    #   faker
    #   matplotlib
    #   pandas
-python-dotenv==1.1.1
+python-discovery==1.1.1
+    # via virtualenv
+python-dotenv==1.2.2
    # via uvicorn
-pytz==2025.2
+pytz==2026.1.post1
    # via pandas
 pyyaml==6.0.3
    # via
@@ -609,13 +547,10 @@ pyyaml==6.0.3
    #   draccus
    #   hebi-py
    #   huggingface-hub
-    #   jupytext
-    #   omegaconf
    #   peft
    #   pre-commit
    #   pyngrok
    #   pyyaml-include
-    #   timm
    #   transformers
    #   uvicorn
    #   wandb
@@ -625,15 +560,13 @@ pyzmq==27.1.0
    # via
    #   lerobot
    #   meshcat
-reachy2-sdk==1.0.14
+qwen-vl-utils==0.0.14
+    # via lerobot
+reachy2-sdk==1.0.15
    # via lerobot
 reachy2-sdk-api==1.0.21
    # via reachy2-sdk
-referencing==0.37.0
-    # via
-    #   jsonschema
-    #   jsonschema-specifications
-regex==2025.10.23
+regex==2026.2.28
    # via
    #   diffusers
    #   transformers
@@ -642,184 +575,150 @@ requests==2.32.5
    #   datasets
    #   diffusers
    #   dm-control
-    #   huggingface-hub
+    #   qwen-vl-utils
    #   teleop
-    #   transformers
    #   wandb
-rerun-sdk==0.26.1
+rerun-sdk==0.26.2
    # via lerobot
 rhoban-cmeel-jsoncpp==1.9.4.9
    # via placo
-robomimic==0.2.0
-    # via libero
-robosuite==1.4.0
-    # via libero
-rpds-py==0.28.0
-    # via
-    #   jsonschema
-    #   referencing
-safetensors==0.6.2
+rich==14.3.3
+    # via typer
+safetensors==0.7.0
    # via
    #   accelerate
    #   diffusers
    #   lerobot
    #   peft
-    #   timm
    #   transformers
 scikit-image==0.25.2
    # via
    #   gym-pusht
    #   lerobot
-scipy==1.15.3
+scipy==1.17.1
    # via
    #   dm-control
+    #   lerobot
    #   metaworld
-    #   robosuite
    #   scikit-image
-sentry-sdk==2.42.1
+    #   torchdiffeq
+sentry-sdk==2.54.0
    # via wandb
 shapely==2.1.2
    # via gym-pusht
+shellingham==1.5.4
+    # via typer
 six==1.17.0
    # via
    #   pynput
    #   python-dateutil
-smmap==5.0.2
+smmap==5.0.3
    # via gitdb
-sniffio==1.3.1
-    # via anyio
 stack-data==0.6.3
    # via ipython
-starlette==0.48.0
+starlette==0.52.1
    # via fastapi
 sympy==1.14.0
    # via torch
-teleop==0.1.2
+teleop==0.1.4
    # via lerobot
-tensorboard==2.20.0
-    # via robomimic
-tensorboard-data-server==0.7.2
-    # via tensorboard
-tensorboardx==2.6.4
-    # via robomimic
-termcolor==3.1.0
-    # via
-    #   lerobot
-    #   robomimic
-thop==0.1.1.post2209072238
-    # via libero
-tifffile==2025.5.10
+termcolor==3.3.0
+    # via lerobot
+tifffile==2026.3.3
    # via scikit-image
-timm==1.0.20
-    # via lerobot
-tokenizers==0.22.1
+tokenizers==0.22.2
    # via transformers
 toml==0.10.2
    # via draccus
-tomli==2.3.0
-    # via
-    #   cmeel
-    #   coverage
-    #   jupytext
-    #   pytest
-torch==2.7.1
+torch==2.10.0
    # via
    #   accelerate
    #   lerobot
    #   peft
-    #   robomimic
-    #   thop
-    #   timm
+    #   torchdiffeq
    #   torchvision
-torchcodec==0.5
+torchcodec==0.10.0
    # via lerobot
-torchvision==0.22.1
-    # via
-    #   lerobot
-    #   robomimic
-    #   timm
-tornado==6.5.2
+torchdiffeq==0.2.5
+    # via lerobot
+torchvision==0.25.0
+    # via lerobot
+tornado==6.5.4
    # via meshcat
-tqdm==4.67.1
+tqdm==4.67.3
    # via
    #   datasets
    #   dm-control
    #   huggingface-hub
    #   peft
-    #   robomimic
    #   transformers
 traitlets==5.14.3
    # via
    #   ipython
-    #   jupyter-core
    #   matplotlib-inline
-    #   nbformat
-transformers==4.57.1
+transformers==5.3.0
    # via
    #   lerobot
-    #   libero
    #   peft
 transforms3d==0.4.2
    # via teleop
+typer==0.24.1
+    # via
+    #   huggingface-hub
+    #   transformers
 typing-extensions==4.15.0
    # via
    #   aiosignal
    #   anyio
    #   etils
-    #   exceptiongroup
+    #   faker
    #   fastapi
    #   gymnasium
    #   huggingface-hub
-    #   ipython
-    #   multidict
+    #   mypy
    #   pydantic
    #   pydantic-core
-    #   referencing
    #   rerun-sdk
    #   starlette
    #   torch
    #   typing-inspect
    #   typing-inspection
-    #   uvicorn
-    #   virtualenv
    #   wandb
 typing-inspect==0.9.0
    # via draccus
 typing-inspection==0.4.2
-    # via pydantic
-tzdata==2025.2
+    # via
+    #   fastapi
+    #   pydantic
+tzdata==2025.3
    # via pandas
 u-msgpack-python==2.8.0
    # via meshcat
-urllib3==2.5.0
+urllib3==2.6.3
    # via
    #   requests
    #   sentry-sdk
-uvicorn[standard]==0.38.0
+uvicorn[standard]==0.41.0
    # via teleop
 uvloop==0.22.1
    # via uvicorn
-virtualenv==20.35.3
+virtualenv==21.1.0
    # via pre-commit
-wandb==0.21.4
-    # via
-    #   lerobot
-    #   libero
+wandb==0.24.2
+    # via lerobot
 watchfiles==1.1.1
    # via uvicorn
-wcwidth==0.2.14
+wcwidth==0.6.0
    # via prompt-toolkit
 websocket-client==1.9.0
    # via teleop
-websockets==15.0.1
+websockets==16.0
    # via uvicorn
-werkzeug==3.1.3
-    # via tensorboard
-wrapt==2.0.0
+wrapt==2.1.2
    # via dm-tree
 xxhash==3.6.0
    # via datasets
-yarl==1.22.0
+yarl==1.23.0
    # via aiohttp
 zipp==3.23.0
    # via
@@ -1,12 +1,12 @@
 #
-# This file is autogenerated by pip-compile with Python 3.10
+# This file is autogenerated by pip-compile with Python 3.12
 # by the following command:
 #
 #    pip-compile --output-file=requirements-ubuntu.txt requirements.in
 #
 -e .[all]
    # via -[all]
-absl-py==2.3.1
+absl-py==2.4.0
    # via
    #   dm-control
    #   dm-env
@@ -14,30 +14,33 @@ absl-py==2.3.1
    #   labmaze
    #   mujoco
    #   tensorboard
-accelerate==1.11.0
+accelerate==1.13.0
    # via
    #   lerobot
    #   peft
 aiohappyeyeballs==2.6.1
    # via aiohttp
-aiohttp==3.13.1
+aiohttp==3.13.3
    # via fsspec
 aiosignal==1.4.0
    # via aiohttp
+annotated-doc==0.0.4
+    # via
+    #   fastapi
+    #   typer
 annotated-types==0.7.0
    # via pydantic
 antlr4-python3-runtime==4.9.3
    # via
    #   hydra-core
    #   omegaconf
-anyio==4.11.0
+anyio==4.12.1
    # via
+    #   httpx
    #   starlette
    #   watchfiles
-asttokens==3.0.0
+asttokens==3.0.1
    # via stack-data
-async-timeout==5.0.1
-    # via aiohttp
 attrs==25.4.0
    # via
    #   aiohttp
@@ -47,30 +50,35 @@ attrs==25.4.0
    #   referencing
    #   rerun-sdk
 av==15.1.0
-    # via lerobot
-bddl==1.0.1
-    # via libero
-certifi==2025.10.5
    # via
+    #   lerobot
+    #   qwen-vl-utils
+bddl==1.0.1
+    # via hf-libero
+certifi==2026.2.25
+    # via
+    #   httpcore
+    #   httpx
    #   requests
    #   sentry-sdk
 cffi==2.0.0
    # via pymunk
-cfgv==3.4.0
+cfgv==3.5.0
    # via pre-commit
-charset-normalizer==3.4.4
+charset-normalizer==3.4.5
    # via requests
-click==8.3.0
+click==8.3.1
    # via
+    #   typer
    #   uvicorn
    #   wandb
-cloudpickle==3.1.1
+cloudpickle==3.1.2
    # via
    #   gymnasium
-    #   libero
-cmake==4.1.0
+    #   hf-libero
+cmake==4.1.3
    # via lerobot
-cmeel==0.57.3
+cmeel==0.59.0
    # via
    #   cmeel-assimp
    #   cmeel-boost
@@ -108,20 +116,24 @@ cmeel-zlib==1.3.1
    # via cmeel-assimp
 coal-library==3.0.1
    # via pin
-contourpy==1.3.2
-    # via matplotlib
-coverage[toml]==7.11.0
+contourpy==1.3.3
+    # via
+    #   lerobot
+    #   matplotlib
+coverage[toml]==7.13.4
    # via pytest-cov
+cuda-bindings==12.9.4
+    # via torch
+cuda-pathfinder==1.4.1
+    # via cuda-bindings
 cycler==0.12.1
    # via matplotlib
-datasets==4.1.1
+datasets==4.6.1
    # via lerobot
-debugpy==1.8.17
+debugpy==1.8.20
    # via lerobot
 decorator==5.2.1
    # via ipython
-decord==0.6.0
-    # via lerobot
 deepdiff==8.6.1
    # via lerobot
 diffusers==0.35.2
@@ -132,7 +144,7 @@ dill==0.4.0
    #   multiprocess
 distlib==0.4.0
    # via virtualenv
-dm-control==1.0.34
+dm-control==1.0.37
    # via gym-aloha
 dm-env==1.6
    # via dm-control
@@ -140,7 +152,6 @@ dm-tree==0.1.9
    # via
    #   dm-control
    #   dm-env
-    #   lerobot
 docopt==0.6.2
    # via num2words
 draccus==0.10.0
@@ -148,66 +159,60 @@ draccus==0.10.0
 dynamixel-sdk==3.8.4
    # via lerobot
 easydict==1.13
-    # via libero
-egl-probe @ git+https://github.com/huggingface/egl_probe.git
-    # via
-    #   libero
-    #   robomimic
+    # via hf-libero
+egl-probe==1.0.2
+    # via robomimic
 eigenpy==3.10.3
    # via coal-library
-einops==0.8.1
+einops==0.8.2
    # via
-    #   flash-attn
+    #   hf-libero
    #   lerobot
-    #   libero
 eiquadprog==1.2.9
    # via placo
-etils[epath,epy]==1.13.0
+etils[epath,epy]==1.14.0
    # via mujoco
-evdev==1.9.2
+evdev==1.9.3
    # via pynput
-exceptiongroup==1.3.0
-    # via
-    #   anyio
-    #   ipython
-    #   pytest
 executing==2.2.1
    # via stack-data
+faker==34.0.2
+    # via lerobot
 farama-notifications==0.0.4
    # via gymnasium
-fastapi==0.119.1
-    # via teleop
+fastapi==0.135.1
+    # via
+    #   lerobot
+    #   teleop
 fastjsonschema==2.21.2
    # via nbformat
 feetech-servo-sdk==1.0.0
    # via lerobot
-filelock==3.20.0
+filelock==3.25.0
    # via
    #   datasets
    #   diffusers
    #   huggingface-hub
+    #   python-discovery
    #   torch
-    #   transformers
    #   virtualenv
-flash-attn==2.8.3
-    # via lerobot
-fonttools==4.60.1
+fonttools==4.61.1
    # via matplotlib
 frozenlist==1.8.0
    # via
    #   aiohttp
    #   aiosignal
-fsspec[http]==2025.9.0
+fsspec[http]==2026.2.0
    # via
    #   datasets
    #   etils
    #   huggingface-hub
    #   torch
 future==1.0.0
-    # via libero
+    # via hf-libero
 gitdb==4.0.12
    # via gitpython
-gitpython==3.1.45
+gitpython==3.1.46
    # via wandb
 glfw==2.10.0
    # via
@@ -230,50 +235,60 @@ gym-hil==0.1.13
    # via lerobot
 gym-pusht==0.1.6
    # via lerobot
-gymnasium==1.2.1
+gymnasium==1.2.3
    # via
    #   gym-aloha
    #   gym-hil
    #   gym-pusht
+    #   hf-libero
    #   lerobot
-    #   libero
    #   metaworld
 h11==0.16.0
-    # via uvicorn
-h5py==3.15.1
+    # via
+    #   httpcore
+    #   uvicorn
+h5py==3.16.0
    # via robomimic
 hebi-py==2.11.0
    # via lerobot
-hf-transfer==0.1.9
-    # via huggingface-hub
-hf-xet==1.1.10
+hf-egl-probe==1.0.2
+    # via hf-libero
+hf-libero==0.1.3
+    # via lerobot
+hf-xet==1.3.2
    # via huggingface-hub
 hidapi==0.14.0.post4
    # via
    #   gym-hil
    #   lerobot
+httpcore==1.0.9
+    # via httpx
 httptools==0.7.1
    # via uvicorn
-huggingface-hub[cli,hf-transfer]==0.35.3
+httpx==0.28.1
+    # via
+    #   datasets
+    #   huggingface-hub
+huggingface-hub==1.6.0
    # via
    #   accelerate
    #   datasets
    #   diffusers
    #   lerobot
    #   peft
-    #   timm
    #   tokenizers
    #   transformers
 hydra-core==1.3.2
-    # via libero
-identify==2.6.15
+    # via hf-libero
+identify==2.6.17
    # via pre-commit
 idna==3.11
    # via
    #   anyio
+    #   httpx
    #   requests
    #   yarl
-imageio[ffmpeg]==2.37.0
+imageio[ffmpeg]==2.37.2
    # via
    #   gym-aloha
    #   gym-hil
@@ -285,16 +300,14 @@ imageio-ffmpeg==0.6.0
    # via
    #   imageio
    #   robomimic
-importlib-metadata==8.7.0
+importlib-metadata==8.7.1
    # via diffusers
-importlib-resources==6.5.2
-    # via etils
 iniconfig==2.3.0
    # via pytest
-inquirerpy==0.3.4
-    # via huggingface-hub
-ipython==8.37.0
+ipython==9.11.0
    # via meshcat
+ipython-pygments-lexers==1.1.1
+    # via ipython
 ischedule==1.2.7
    # via placo
 jedi==0.19.2
@@ -303,40 +316,41 @@ jinja2==3.1.6
    # via torch
 jsonlines==4.0.0
    # via lerobot
-jsonschema==4.25.1
+jsonschema==4.26.0
    # via nbformat
 jsonschema-specifications==2025.9.1
    # via jsonschema
 jupyter-core==5.9.1
    # via nbformat
-jupytext==1.18.1
+jupytext==1.19.1
    # via bddl
 kiwisolver==1.4.9
    # via matplotlib
 labmaze==1.0.6
    # via dm-control
-lazy-loader==0.4
+lazy-loader==0.5
    # via scikit-image
-libero @ git+https://github.com/huggingface/lerobot-libero.git@main
-    # via lerobot
-llvmlite==0.45.1
+librt==0.8.1
+    # via mypy
+llvmlite==0.46.0
    # via numba
 lxml==6.0.2
    # via dm-control
-markdown==3.9
+markdown==3.10.2
    # via tensorboard
 markdown-it-py==4.0.0
    # via
    #   jupytext
    #   mdit-py-plugins
+    #   rich
 markupsafe==3.0.3
    # via
    #   jinja2
    #   werkzeug
-matplotlib==3.10.7
+matplotlib==3.10.8
    # via
+    #   hf-libero
    #   lerobot
-    #   libero
 matplotlib-inline==0.2.1
    # via ipython
 mdit-py-plugins==0.5.0
@@ -353,36 +367,38 @@ mock-serial==0.0.1
    # via lerobot
 mpmath==1.3.0
    # via sympy
-mujoco==3.3.7
+mujoco==3.5.0
    # via
    #   dm-control
    #   gym-aloha
    #   gym-hil
-    #   libero
+    #   hf-libero
    #   metaworld
    #   robosuite
-multidict==6.7.0
+multidict==6.7.1
    # via
    #   aiohttp
    #   yarl
-multiprocess==0.70.16
+multiprocess==0.70.18
    # via datasets
+mypy==1.19.1
+    # via lerobot
 mypy-extensions==1.1.0
-    # via typing-inspect
+    # via
+    #   mypy
+    #   typing-inspect
 nbformat==5.10.4
    # via jupytext
-networkx==3.4.2
+networkx==3.6.1
    # via
    #   bddl
    #   scikit-image
    #   torch
-ninja==1.13.0
-    # via lerobot
-nodeenv==1.9.1
+nodeenv==1.10.0
    # via pre-commit
 num2words==0.5.14
    # via lerobot
-numba==0.62.1
+numba==0.64.0
    # via robosuite
 numpy==2.2.6
    # via
@@ -391,7 +407,6 @@ numpy==2.2.6
    #   cmeel-boost
    #   contourpy
    #   datasets
-    #   decord
    #   diffusers
    #   dm-control
    #   dm-env
@@ -399,9 +414,10 @@ numpy==2.2.6
    #   gymnasium
    #   h5py
    #   hebi-py
+    #   hf-libero
    #   imageio
    #   labmaze
-    #   libero
+    #   lerobot
    #   matplotlib
    #   meshcat
    #   metaworld
@@ -426,49 +442,51 @@ numpy==2.2.6
    #   torchvision
    #   transformers
    #   transforms3d
-nvidia-cublas-cu12==12.6.4.1
+nvidia-cublas-cu12==12.8.4.1
    # via
    #   nvidia-cudnn-cu12
    #   nvidia-cusolver-cu12
    #   torch
-nvidia-cuda-cupti-cu12==12.6.80
+nvidia-cuda-cupti-cu12==12.8.90
    # via torch
-nvidia-cuda-nvrtc-cu12==12.6.77
+nvidia-cuda-nvrtc-cu12==12.8.93
    # via torch
-nvidia-cuda-runtime-cu12==12.6.77
+nvidia-cuda-runtime-cu12==12.8.90
    # via torch
-nvidia-cudnn-cu12==9.5.1.17
+nvidia-cudnn-cu12==9.10.2.21
    # via torch
-nvidia-cufft-cu12==11.3.0.4
+nvidia-cufft-cu12==11.3.3.83
    # via torch
-nvidia-cufile-cu12==1.11.1.6
+nvidia-cufile-cu12==1.13.1.3
    # via torch
-nvidia-curand-cu12==10.3.7.77
+nvidia-curand-cu12==10.3.9.90
    # via torch
-nvidia-cusolver-cu12==11.7.1.2
+nvidia-cusolver-cu12==11.7.3.90
    # via torch
-nvidia-cusparse-cu12==12.5.4.2
+nvidia-cusparse-cu12==12.5.8.93
    # via
    #   nvidia-cusolver-cu12
    #   torch
-nvidia-cusparselt-cu12==0.6.3
+nvidia-cusparselt-cu12==0.7.1
    # via torch
-nvidia-nccl-cu12==2.26.2
+nvidia-nccl-cu12==2.27.5
    # via torch
-nvidia-nvjitlink-cu12==12.6.85
+nvidia-nvjitlink-cu12==12.8.93
    # via
    #   nvidia-cufft-cu12
    #   nvidia-cusolver-cu12
    #   nvidia-cusparse-cu12
    #   torch
-nvidia-nvtx-cu12==12.6.77
+nvidia-nvshmem-cu12==3.4.5
+    # via torch
+nvidia-nvtx-cu12==12.8.90
    # via torch
 omegaconf==2.3.0
    # via hydra-core
-opencv-python==4.12.0.88
+opencv-python==4.13.0.92
    # via
    #   gym-pusht
-    #   libero
+    #   hf-libero
    #   reachy2-sdk
    #   robosuite
 opencv-python-headless==4.12.0.88
@@ -487,6 +505,7 @@ packaging==25.0
    #   matplotlib
    #   peft
    #   pytest
+    #   qwen-vl-utils
    #   reachy2-sdk
    #   scikit-image
    #   tensorboard
@@ -497,21 +516,21 @@ pandas==2.3.3
    # via
    #   datasets
    #   lerobot
-parso==0.8.5
+parso==0.8.6
    # via jedi
-peft==0.17.1
+pathspec==1.0.4
+    # via mypy
+peft==0.18.1
    # via lerobot
 pexpect==4.9.0
    # via ipython
-pfzy==0.3.4
-    # via inquirerpy
-pillow==12.0.0
+pillow==12.1.1
    # via
    #   diffusers
    #   imageio
-    #   lerobot
    #   matplotlib
    #   meshcat
+    #   qwen-vl-utils
    #   rerun-sdk
    #   robosuite
    #   scikit-image
@@ -519,28 +538,27 @@ pillow==12.0.0
    #   torchvision
 pin==3.4.0
    # via placo
-placo==0.9.14
+placo==0.9.16
    # via lerobot
-platformdirs==4.5.0
+platformdirs==4.9.4
    # via
    #   jupyter-core
+    #   python-discovery
    #   virtualenv
    #   wandb
 pluggy==1.6.0
    # via
    #   pytest
    #   pytest-cov
-pre-commit==4.3.0
+pre-commit==4.5.1
    # via lerobot
 prompt-toolkit==3.0.52
-    # via
-    #   inquirerpy
-    #   ipython
+    # via ipython
 propcache==0.4.1
    # via
    #   aiohttp
    #   yarl
-protobuf==6.31.0
+protobuf==6.31.1
    # via
    #   dm-control
    #   grpcio-tools
@@ -550,7 +568,7 @@ protobuf==6.31.0
    #   tensorboard
    #   tensorboardx
    #   wandb
-psutil==7.1.1
+psutil==7.2.2
    # via
    #   accelerate
    #   imageio
@@ -560,17 +578,17 @@ ptyprocess==0.7.0
    # via pexpect
 pure-eval==0.2.3
    # via stack-data
-pyarrow==21.0.0
+pyarrow==23.0.1
    # via
    #   datasets
    #   rerun-sdk
-pycparser==2.23
+pycparser==3.0
    # via cffi
-pydantic==2.12.3
+pydantic==2.12.5
    # via
    #   fastapi
    #   wandb
-pydantic-core==2.41.4
+pydantic-core==2.41.5
    # via pydantic
 pygame==2.6.1
    # via
@@ -580,12 +598,14 @@ pygame==2.6.1
 pygments==2.19.2
    # via
    #   ipython
+    #   ipython-pygments-lexers
    #   pytest
+    #   rich
 pymunk==6.11.1
    # via
    #   gym-pusht
    #   lerobot
-pyngrok==7.4.1
+pyngrok==7.5.1
    # via meshcat
 pynput==1.8.1
    # via
@@ -595,7 +615,7 @@ pyopengl==3.1.10
    # via
    #   dm-control
    #   mujoco
-pyparsing==3.2.5
+pyparsing==3.3.2
    # via
    #   dm-control
    #   matplotlib
@@ -621,13 +641,16 @@ pytest-timeout==2.4.0
    # via lerobot
 python-dateutil==2.9.0.post0
    # via
+    #   faker
    #   matplotlib
    #   pandas
-python-dotenv==1.1.1
+python-discovery==1.1.1
+    # via virtualenv
+python-dotenv==1.2.2
    # via uvicorn
 python-xlib==0.33
    # via pynput
-pytz==2025.2
+pytz==2026.1.post1
    # via pandas
 pyyaml==6.0.3
    # via
@@ -642,7 +665,6 @@ pyyaml==6.0.3
    #   pre-commit
    #   pyngrok
    #   pyyaml-include
-    #   timm
    #   transformers
    #   uvicorn
    #   wandb
@@ -652,7 +674,9 @@ pyzmq==27.1.0
    # via
    #   lerobot
    #   meshcat
-reachy2-sdk==1.0.14
+qwen-vl-utils==0.0.14
+    # via lerobot
+reachy2-sdk==1.0.15
    # via lerobot
 reachy2-sdk-api==1.0.21
    # via reachy2-sdk
@@ -660,7 +684,7 @@ referencing==0.37.0
    # via
    #   jsonschema
    #   jsonschema-specifications
-regex==2025.10.23
+regex==2026.2.28
    # via
    #   diffusers
    #   transformers
@@ -669,60 +693,62 @@ requests==2.32.5
    #   datasets
    #   diffusers
    #   dm-control
-    #   huggingface-hub
+    #   qwen-vl-utils
    #   teleop
-    #   transformers
    #   wandb
-rerun-sdk==0.26.1
+rerun-sdk==0.26.2
    # via lerobot
 rhoban-cmeel-jsoncpp==1.9.4.9
    # via placo
+rich==14.3.3
+    # via typer
 robomimic==0.2.0
-    # via libero
+    # via hf-libero
 robosuite==1.4.0
-    # via libero
-rpds-py==0.28.0
+    # via hf-libero
+rpds-py==0.30.0
    # via
    #   jsonschema
    #   referencing
-safetensors==0.6.2
+safetensors==0.7.0
    # via
    #   accelerate
    #   diffusers
    #   lerobot
    #   peft
-    #   timm
    #   transformers
 scikit-image==0.25.2
    # via
    #   gym-pusht
    #   lerobot
-scipy==1.15.3
+scipy==1.17.1
    # via
    #   dm-control
+    #   lerobot
    #   metaworld
    #   robosuite
    #   scikit-image
-sentry-sdk==2.42.1
+    #   torchdiffeq
+sentry-sdk==2.54.0
    # via wandb
 shapely==2.1.2
    # via gym-pusht
+shellingham==1.5.4
+    # via typer
 six==1.17.0
    # via
    #   pynput
    #   python-dateutil
    #   python-xlib
-smmap==5.0.2
+smmap==5.0.3
    # via gitdb
-sniffio==1.3.1
-    # via anyio
 stack-data==0.6.3
    # via ipython
-starlette==0.48.0
+starlette==0.52.1
    # via fastapi
 sympy==1.14.0
    # via torch
-teleop==0.1.2
+teleop==0.1.4
    # via lerobot
 tensorboard==2.20.0
    # via robomimic
@@ -730,46 +756,38 @@ tensorboard-data-server==0.7.2
    # via tensorboard
 tensorboardx==2.6.4
    # via robomimic
-termcolor==3.1.0
+termcolor==3.3.0
    # via
    #   lerobot
    #   robomimic
 thop==0.1.1.post2209072238
-    # via libero
-tifffile==2025.5.10
+    # via hf-libero
+tifffile==2026.3.3
    # via scikit-image
-timm==1.0.20
-    # via lerobot
-tokenizers==0.22.1
+tokenizers==0.22.2
    # via transformers
 toml==0.10.2
    # via draccus
-tomli==2.3.0
-    # via
-    #   cmeel
-    #   coverage
-    #   jupytext
-    #   pytest
-torch==2.7.1
+torch==2.10.0
    # via
    #   accelerate
-    #   flash-attn
    #   lerobot
    #   peft
    #   robomimic
    #   thop
-    #   timm
+    #   torchdiffeq
    #   torchvision
-torchcodec==0.5
+torchcodec==0.10.0
    # via lerobot
-torchvision==0.22.1
+torchdiffeq==0.2.5
+    # via lerobot
+torchvision==0.25.0
    # via
    #   lerobot
    #   robomimic
-    #   timm
-tornado==6.5.2
+tornado==6.5.4
    # via meshcat
-tqdm==4.67.1
+tqdm==4.67.3
    # via
    #   datasets
    #   dm-control
@@ -783,26 +801,29 @@ traitlets==5.14.3
    #   jupyter-core
    #   matplotlib-inline
    #   nbformat
-transformers==4.57.1
+transformers==5.3.0
    # via
+    #   hf-libero
    #   lerobot
-    #   libero
    #   peft
 transforms3d==0.4.2
    # via teleop
-triton==3.3.1
+triton==3.6.0
    # via torch
+typer==0.24.1
+    # via
+    #   huggingface-hub
+    #   transformers
 typing-extensions==4.15.0
    # via
    #   aiosignal
    #   anyio
    #   etils
-    #   exceptiongroup
+    #   faker
    #   fastapi
    #   gymnasium
    #   huggingface-hub
-    #   ipython
-    #   multidict
+    #   mypy
    #   pydantic
    #   pydantic-core
    #   referencing
@@ -811,46 +832,46 @@ typing-extensions==4.15.0
    #   torch
    #   typing-inspect
    #   typing-inspection
-    #   uvicorn
-    #   virtualenv
    #   wandb
 typing-inspect==0.9.0
    # via draccus
 typing-inspection==0.4.2
-    # via pydantic
-tzdata==2025.2
+    # via
+    #   fastapi
+    #   pydantic
+tzdata==2025.3
    # via pandas
 u-msgpack-python==2.8.0
    # via meshcat
-urllib3==2.5.0
+urllib3==2.6.3
    # via
    #   requests
    #   sentry-sdk
-uvicorn[standard]==0.38.0
+uvicorn[standard]==0.41.0
    # via teleop
 uvloop==0.22.1
    # via uvicorn
-virtualenv==20.35.3
+virtualenv==21.1.0
    # via pre-commit
-wandb==0.21.4
+wandb==0.24.2
    # via
+    #   hf-libero
    #   lerobot
-    #   libero
 watchfiles==1.1.1
    # via uvicorn
-wcwidth==0.2.14
+wcwidth==0.6.0
    # via prompt-toolkit
 websocket-client==1.9.0
    # via teleop
-websockets==15.0.1
+websockets==16.0
    # via uvicorn
-werkzeug==3.1.3
+werkzeug==3.1.6
    # via tensorboard
-wrapt==2.0.0
+wrapt==2.1.2
    # via dm-tree
 xxhash==3.6.0
    # via datasets
-yarl==1.22.0
+yarl==1.23.0
    # via aiohttp
 zipp==3.23.0
    # via
@@ -1,9 +1,9 @@
 # requirements.in

-# requirements-macos.txt was generated on macOS and is platform-specific (macOS 26.0.1 25A362 arm64).
-# Darwin MacBook-Pro.local 25.0.0 Darwin Kernel Version 25.0.0: Wed Sep 17 21:42:08 PDT 2025; root:xnu-12377.1.9~141/RELEASE_ARM64_T8132 arm64
+# requirements-macos.txt was generated on macOS and is platform-specific (macOS 26.3.1 25D2128 arm64).
+# Darwin MacBook-Pro.local 25.3.0 Darwin Kernel Version 25.3.0: Wed Jan 28 20:54:55 PST 2026; root:xnu-12377.91.3~2/RELEASE_ARM64_T8132 arm64

-# requirements-ubuntu.txt was generated on Linux and is platform-specific (Ubuntu 24.04.3 LTS x86_64).
-# Linux mlerobot-linux 6.14.0-33-generic #33~24.04.1-Ubuntu SMP PREEMPT_DYNAMIC Fri Sep 19 17:02:30 UTC 2 x86_64 x86_64 x86_64 GNU/Linux
+# requirements-ubuntu.txt was generated on Linux and is platform-specific (Ubuntu 24.04.4 LTS x86_64).
+# Linux lerobot-linux 6.17.0-14-generic #14~24.04.1-Ubuntu SMP PREEMPT_DYNAMIC Thu Jan 15 15:52:10 UTC 2 x86_64 x86_64 x86_64 GNU/Linux

 -e .[all]
@@ -49,9 +49,14 @@ import torch

 from lerobot.cameras.opencv.configuration_opencv import OpenCVCameraConfig  # noqa: F401
 from lerobot.cameras.realsense.configuration_realsense import RealSenseCameraConfig  # noqa: F401
-from lerobot.robots import (
-    RobotConfig,  # noqa: F401
+from lerobot.robots import (  # noqa: F401
+    Robot,
+    RobotConfig,
+    bi_so_follower,
+    koch_follower,
    make_robot_from_config,
+    omx_follower,
+    so_follower,
 )
 from lerobot.transport import (
    services_pb2,  # type: ignore
@@ -181,7 +181,7 @@ class ZMQCamera(Camera):
        try:
            message = self.socket.recv_string()
        except Exception as e:
-            # Check for ZMQ timeout (EAGAIN/Again) without requiring global zmq import
+            # zmq is lazy-imported in connect(), so check by name to avoid a top-level import
            if type(e).__name__ == "Again":
                raise TimeoutError(f"{self} timeout after {self.timeout_ms}ms") from e
            raise
@@ -23,6 +23,7 @@ import base64
 import contextlib
 import json
 import logging
+import threading
 import time
 from collections import deque

@@ -42,10 +43,57 @@ def encode_image(image: np.ndarray, quality: int = 80) -> str:
    return base64.b64encode(buffer).decode("utf-8")


+class CameraCaptureThread:
+    """Background thread that continuously captures and encodes frames from a camera."""
+
+    def __init__(self, camera: OpenCVCamera, name: str):
+        self.camera = camera
+        self.name = name
+        self.latest_encoded: str | None = None  # Pre-encoded JPEG as base64
+        self.latest_timestamp: float = 0.0
+        self.frame_lock = threading.Lock()
+        self.running = False
+        self.thread: threading.Thread | None = None
+
+    def start(self):
+        """Start the capture thread."""
+        self.running = True
+        self.thread = threading.Thread(target=self._capture_loop, daemon=True)
+        self.thread.start()
+
+    def stop(self):
+        """Stop the capture thread."""
+        self.running = False
+        if self.thread:
+            self.thread.join(timeout=1.0)
+
+    def _capture_loop(self):
+        """Continuously capture and encode frames at the camera's native rate."""
+        while self.running:
+            try:
+                frame = self.camera.read()  # Blocks at camera's native rate
+                timestamp = time.time()
+                # Encode immediately in capture thread (this is the slow part)
+                encoded = encode_image(frame)
+                with self.frame_lock:
+                    self.latest_encoded = encoded
+                    self.latest_timestamp = timestamp
+            except Exception as e:
+                logger.warning(f"Camera {self.name} capture error: {e}")
+                time.sleep(0.01)
+
+    def get_latest(self) -> tuple[str | None, float]:
+        """Get the latest encoded frame and its timestamp."""
+        with self.frame_lock:
+            return self.latest_encoded, self.latest_timestamp
+
+
 class ImageServer:
    def __init__(self, config: dict, port: int = 5555):
+        # fps controls the publish loop rate (how often frames are sent over ZMQ), not the camera capture rate
        self.fps = config.get("fps", 30)
        self.cameras: dict[str, OpenCVCamera] = {}
+        self.capture_threads: dict[str, CameraCaptureThread] = {}

        for name, cfg in config.get("cameras", {}).items():
            shape = cfg.get("shape", [480, 640])
@@ -61,6 +109,10 @@ class ImageServer:
            self.cameras[name] = camera
            logger.info(f"Camera {name}: {shape[1]}x{shape[0]}")

+            # Create capture thread for this camera
+            capture_thread = CameraCaptureThread(camera, name)
+            self.capture_threads[name] = capture_thread
+
        # ZMQ PUB socket
        self.context = zmq.Context()
        self.socket = self.context.socket(zmq.PUB)
@@ -73,6 +125,18 @@ class ImageServer:
    def run(self):
        frame_count = 0
        frame_times = deque(maxlen=60)
+        last_published_ts: dict[str, float] = {}
+
+        # Start all capture threads
+        for capture_thread in self.capture_threads.values():
+            capture_thread.start()
+
+        # Wait for first frames to be captured and encoded
+        logger.info("Waiting for cameras to start capturing...")
+        for name, capture_thread in self.capture_threads.items():
+            while capture_thread.get_latest()[0] is None:
+                time.sleep(0.01)
+            logger.info(f"Camera {name} ready (capture + encode in background)")

        try:
            while True:
@@ -80,10 +144,12 @@ class ImageServer:

                # Build message
                message = {"timestamps": {}, "images": {}}
-                for name, cam in self.cameras.items():
-                    frame = cam.read()  # Returns RGB
-                    message["timestamps"][name] = time.time()
-                    message["images"][name] = encode_image(frame)
+                for name, capture_thread in self.capture_threads.items():
+                    encoded, timestamp = capture_thread.get_latest()
+                    if encoded is not None and timestamp > last_published_ts.get(name, 0.0):
+                        message["timestamps"][name] = timestamp
+                        message["images"][name] = encoded
+                        last_published_ts[name] = timestamp

                # Send as JSON string (suppress if buffer full)
                with contextlib.suppress(zmq.Again):
@@ -102,6 +168,8 @@ class ImageServer:
        except KeyboardInterrupt:
            pass
        finally:
+            for capture_thread in self.capture_threads.values():
+                capture_thread.stop()
            for cam in self.cameras.values():
                cam.disconnect()
            self.socket.close()
@@ -50,6 +50,9 @@ class TrainPipelineConfig(HubMixin):
    # `seed` is used for training (eg: model initialization, dataset shuffling)
    # AND for the evaluation environments.
    seed: int | None = 1000
+    # Set to True to use deterministic cuDNN algorithms for reproducibility.
+    # This disables cudnn.benchmark and may reduce training speed by ~10-20%.
+    cudnn_deterministic: bool = False
    # Number of workers for the dataloader.
    num_workers: int = 4
    batch_size: int = 8
@@ -346,6 +346,52 @@ class LiberoEnv(EnvConfig):
        return kwargs


+@EnvConfig.register_subclass("robocasa")
+@dataclass
+class RoboCasaEnv(EnvConfig):
+    """RoboCasa kitchen composite-task environments.
+
+    Wraps ``robocasa.wrappers.gym_wrapper.RoboCasaGymEnv`` with a flat 12-D Box
+    action space and a structured pixel + state observation dict.
+
+    Selected benchmark tasks (3 short + 2 long):
+        Short:  PickPlaceCounterToCabinet, PrepareToast, CoffeeSetupMug
+        Long:   PrepareCoffee, RestockPantry
+    """
+
+    task: str = "PickPlaceCounterToCabinet"
+    tasks: list[str] | None = None  # multi-task: list of task names (without robocasa/ prefix)
+    fps: int = 20
+    episode_length: int = 500
+    image_size: int = 128
+    split: str = "target"  # "pretrain" or "target"
+    features: dict[str, PolicyFeature] = field(
+        default_factory=lambda: {
+            ACTION: PolicyFeature(type=FeatureType.ACTION, shape=(12,)),
+        }
+    )
+    features_map: dict[str, str] = field(
+        default_factory=lambda: {
+            ACTION: ACTION,
+            "agentview_left":  f"{OBS_IMAGES}.agentview_left",
+            "agentview_right": f"{OBS_IMAGES}.agentview_right",
+            "eye_in_hand":     f"{OBS_IMAGES}.eye_in_hand",
+            "robot_state":     OBS_STATE,
+        }
+    )
+
+    def __post_init__(self):
+        for cam in ("agentview_left", "agentview_right", "eye_in_hand"):
+            self.features[cam] = PolicyFeature(
+                type=FeatureType.VISUAL, shape=(self.image_size, self.image_size, 3)
+            )
+        self.features["robot_state"] = PolicyFeature(type=FeatureType.STATE, shape=(16,))
+
+    @property
+    def gym_kwargs(self) -> dict:
+        return {"split": self.split}
+
+
@EnvConfig.register_subclass("metaworld")
@dataclass
 class MetaworldEnv(EnvConfig):
@@ -20,11 +20,11 @@ import gymnasium as gym
 from gymnasium.envs.registration import registry as gym_registry

 from lerobot.configs.policies import PreTrainedConfig
-from lerobot.envs.configs import AlohaEnv, EnvConfig, HubEnvConfig, IsaaclabArenaEnv, LiberoEnv, PushtEnv
+from lerobot.envs.configs import AlohaEnv, EnvConfig, HubEnvConfig, IsaaclabArenaEnv, LiberoEnv, PushtEnv, RoboCasaEnv
 from lerobot.envs.utils import _call_make_env, _download_hub_file, _import_hub_module, _normalize_hub_result
 from lerobot.policies.xvla.configuration_xvla import XVLAConfig
 from lerobot.processor import ProcessorStep
-from lerobot.processor.env_processor import IsaaclabArenaProcessorStep, LiberoProcessorStep
+from lerobot.processor.env_processor import IsaaclabArenaProcessorStep, LiberoProcessorStep, RoboCasaProcessorStep
 from lerobot.processor.pipeline import PolicyProcessorPipeline


@@ -35,6 +35,8 @@ def make_env_config(env_type: str, **kwargs) -> EnvConfig:
        return PushtEnv(**kwargs)
    elif env_type == "libero":
        return LiberoEnv(**kwargs)
+    elif env_type == "robocasa":
+        return RoboCasaEnv(**kwargs)
    else:
        raise ValueError(f"Policy type '{env_type}' is not available.")

@@ -73,6 +75,10 @@ def make_env_pre_post_processors(
    if isinstance(env_cfg, LiberoEnv) or "libero" in env_cfg.type:
        preprocessor_steps.append(LiberoProcessorStep())

+    # For RoboCasa environments, add the RoboCasaProcessorStep to preprocessor
+    if isinstance(env_cfg, RoboCasaEnv) or "robocasa" in env_cfg.type:
+        preprocessor_steps.append(RoboCasaProcessorStep())
+
    # For Isaaclab Arena environments, add the IsaaclabArenaProcessorStep
    if isinstance(env_cfg, IsaaclabArenaEnv) or "isaaclab_arena" in env_cfg.type:
        # Parse comma-separated keys (handle None for state-based policies)
@@ -181,6 +187,20 @@ def make_env(
            control_mode=cfg.control_mode,
            episode_length=cfg.episode_length,
        )
+    elif "robocasa" in cfg.type:
+        from lerobot.envs.robocasa import create_robocasa_envs
+
+        tasks = cfg.tasks if cfg.tasks else [cfg.task]
+        return create_robocasa_envs(
+            tasks=tasks,
+            n_envs=n_envs,
+            image_size=cfg.image_size,
+            split=cfg.split,
+            episode_length=cfg.episode_length,
+            gym_kwargs=cfg.gym_kwargs,
+            env_cls=env_cls,
+        )
+
    elif "metaworld" in cfg.type:
        from lerobot.envs.metaworld import create_metaworld_envs

@@ -0,0 +1,273 @@
+#!/usr/bin/env python
+
+# Copyright 2025 The HuggingFace Inc. team. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+from __future__ import annotations
+
+from collections import defaultdict
+from collections.abc import Callable, Sequence
+from functools import partial
+from typing import Any
+
+import gymnasium as gym
+import numpy as np
+from gymnasium import spaces
+
+
+# Action layout (flat 12D, normalized to [-1, 1]):
+#   [0:3]   end_effector_position  (delta x, y, z)
+#   [3:6]   end_effector_rotation  (delta roll, pitch, yaw)
+#   [6:7]   gripper_close          (open=-1, close=+1)
+#   [7:11]  base_motion            (x, y, theta, torso_height)
+#   [11:12] control_mode           (arm=-1, base=+1)
+ACTION_DIM = 12
+ACTION_LOW = -1.0
+ACTION_HIGH = 1.0
+
+# Proprioceptive state layout (flat 16D):
+#   [0:2]   gripper_qpos
+#   [2:5]   base_position
+#   [5:9]   base_rotation (quaternion)
+#   [9:12]  end_effector_position_relative
+#   [12:16] end_effector_rotation_relative (quaternion)
+STATE_DIM = 16
+
+# Obs dict keys from RoboCasaGymEnv.get_observation()
+_CAM_KEYS = (
+    "video.robot0_agentview_left",
+    "video.robot0_agentview_right",
+    "video.robot0_eye_in_hand",
+)
+_STATE_KEYS_ORDERED = (
+    "state.gripper_qpos",           # (2,)
+    "state.base_position",          # (3,)
+    "state.base_rotation",          # (4,)
+    "state.end_effector_position_relative",   # (3,)
+    "state.end_effector_rotation_relative",   # (4,)
+)
+
+# Mapping from video.* key → short image name used in features_map
+CAM_KEY_TO_NAME = {
+    "video.robot0_agentview_left":  "agentview_left",
+    "video.robot0_agentview_right": "agentview_right",
+    "video.robot0_eye_in_hand":     "eye_in_hand",
+}
+
+
+def _flat_to_action_dict(flat: np.ndarray) -> dict[str, np.ndarray]:
+    """Convert a 12D flat action array to the Dict format expected by RoboCasaGymEnv."""
+    return {
+        "action.end_effector_position": flat[0:3],
+        "action.end_effector_rotation": flat[3:6],
+        "action.gripper_close":         flat[6:7],
+        "action.base_motion":           flat[7:11],
+        "action.control_mode":          flat[11:12],
+    }
+
+
+class RoboCasaEnv(gym.Env):
+    """Thin wrapper around RoboCasaGymEnv that provides a flat Box action space
+    and a structured observation dict compatible with LeRobot policies.
+
+    Observations returned by step/reset:
+        {
+            "pixels": {
+                "agentview_left":  (H, W, 3) uint8,
+                "agentview_right": (H, W, 3) uint8,
+                "eye_in_hand":     (H, W, 3) uint8,
+            },
+            "robot_state": (16,) float32,
+        }
+
+    Actions: flat float32 ndarray of shape (12,), normalized to [-1, 1].
+    """
+
+    metadata = {"render_modes": ["rgb_array"], "render_fps": 20}
+
+    def __init__(
+        self,
+        task: str,
+        split: str = "target",
+        image_size: int = 128,
+        render_mode: str = "rgb_array",
+        episode_length: int = 500,
+        **gym_kwargs: Any,
+    ):
+        super().__init__()
+        # Lazy import — robocasa is optional
+        import robocasa.environments  # noqa: F401 — registers all gym envs
+
+        self.task = task
+        self.render_mode = render_mode
+        self.image_size = image_size
+        self._max_episode_steps = episode_length
+        self._step_count = 0
+
+        self._env = gym.make(
+            f"robocasa/{task}",
+            split=split,
+            camera_widths=image_size,
+            camera_heights=image_size,
+            **gym_kwargs,
+        )
+
+        # Flat 12D Box action space
+        self.action_space = spaces.Box(
+            low=ACTION_LOW,
+            high=ACTION_HIGH,
+            shape=(ACTION_DIM,),
+            dtype=np.float32,
+        )
+
+        images = {
+            name: spaces.Box(low=0, high=255, shape=(image_size, image_size, 3), dtype=np.uint8)
+            for name in CAM_KEY_TO_NAME.values()
+        }
+        self.observation_space = spaces.Dict(
+            {
+                "pixels": spaces.Dict(images),
+                "robot_state": spaces.Box(
+                    low=-np.inf, high=np.inf, shape=(STATE_DIM,), dtype=np.float32
+                ),
+            }
+        )
+
+    def _format_obs(self, raw_obs: dict) -> dict:
+        pixels = {
+            CAM_KEY_TO_NAME[k]: raw_obs[k]
+            for k in _CAM_KEYS
+            if k in raw_obs
+        }
+        state_parts = [
+            np.asarray(raw_obs[k], dtype=np.float32)
+            for k in _STATE_KEYS_ORDERED
+            if k in raw_obs
+        ]
+        robot_state = np.concatenate(state_parts) if state_parts else np.zeros(STATE_DIM, dtype=np.float32)
+        return {"pixels": pixels, "robot_state": robot_state}
+
+    def reset(self, seed: int | None = None, **kwargs) -> tuple[dict, dict]:
+        super().reset(seed=seed)
+        self._step_count = 0
+        raw_obs, info = self._env.reset(seed=seed)
+        info.setdefault("is_success", False)
+        info["task"] = self.task
+        return self._format_obs(raw_obs), info
+
+    def step(self, action: np.ndarray) -> tuple[dict, float, bool, bool, dict]:
+        if action.ndim != 1 or action.shape[0] != ACTION_DIM:
+            raise ValueError(
+                f"Expected 1-D action of shape ({ACTION_DIM},), got {action.shape}"
+            )
+        action_dict = _flat_to_action_dict(action)
+        raw_obs, reward, terminated, truncated, info = self._env.step(action_dict)
+        self._step_count += 1
+
+        is_success = bool(info.get("success", False))
+        terminated = terminated or is_success
+        if self._step_count >= self._max_episode_steps:
+            truncated = True
+
+        info.update({"task": self.task, "is_success": is_success})
+        obs = self._format_obs(raw_obs)
+
+        if terminated or truncated:
+            info["final_info"] = {"task": self.task, "is_success": is_success}
+
+        return obs, reward, terminated, truncated, info
+
+    def render(self) -> np.ndarray | None:
+        if self.render_mode == "rgb_array":
+            return self._env.render()
+        return None
+
+    def close(self) -> None:
+        self._env.close()
+
+
+def _make_env_fns(
+    *,
+    task: str,
+    n_envs: int,
+    image_size: int,
+    split: str,
+    episode_length: int,
+    gym_kwargs: dict[str, Any],
+) -> list[Callable[[], RoboCasaEnv]]:
+    """Build n_envs factory callables for a single task."""
+    def _make(episode_index: int) -> RoboCasaEnv:  # noqa: ARG001
+        return RoboCasaEnv(
+            task=task,
+            split=split,
+            image_size=image_size,
+            episode_length=episode_length,
+            **gym_kwargs,
+        )
+
+    return [partial(_make, i) for i in range(n_envs)]
+
+
+def create_robocasa_envs(
+    tasks: str | Sequence[str],
+    n_envs: int,
+    image_size: int = 128,
+    split: str = "target",
+    episode_length: int = 500,
+    gym_kwargs: dict[str, Any] | None = None,
+    env_cls: Callable[[Sequence[Callable[[], Any]]], Any] | None = None,
+) -> dict[str, dict[int, Any]]:
+    """Create vectorized RoboCasa environments.
+
+    Args:
+        tasks: A single task name or list of task names (without "robocasa/" prefix).
+            E.g. "PickPlaceCounterToCabinet" or ["BoilPot", "PrepareCoffee"].
+        n_envs: Number of parallel envs per task.
+        image_size: Square image resolution for all cameras.
+        split: RoboCasa dataset split — "pretrain" or "target".
+        episode_length: Max steps per episode before truncation.
+        gym_kwargs: Extra kwargs forwarded to each RoboCasaEnv.
+        env_cls: Callable to wrap list of factory fns (SyncVectorEnv or AsyncVectorEnv).
+
+    Returns:
+        dict[task_name][task_id=0] -> vec_env
+    """
+    if env_cls is None or not callable(env_cls):
+        raise ValueError("env_cls must be a callable wrapping a list of env factory callables.")
+    if not isinstance(n_envs, int) or n_envs <= 0:
+        raise ValueError(f"n_envs must be a positive int; got {n_envs}.")
+
+    if isinstance(tasks, str):
+        task_list = [t.strip() for t in tasks.split(",") if t.strip()]
+    else:
+        task_list = [str(t).strip() for t in tasks if str(t).strip()]
+    if not task_list:
+        raise ValueError("`tasks` must contain at least one task name.")
+
+    gym_kwargs = dict(gym_kwargs or {})
+    out: dict[str, dict[int, Any]] = defaultdict(dict)
+
+    print(f"Creating RoboCasa envs | tasks={task_list} | n_envs(per task)={n_envs} | split={split}")
+    for task in task_list:
+        fns = _make_env_fns(
+            task=task,
+            n_envs=n_envs,
+            image_size=image_size,
+            split=split,
+            episode_length=episode_length,
+            gym_kwargs=gym_kwargs,
+        )
+        out["robocasa"][len(out["robocasa"])] = env_cls(fns)
+        print(f"  Built vec env | task={task} | n_envs={n_envs}")
+
+    return {suite: dict(task_map) for suite, task_map in out.items()}
@@ -153,6 +153,44 @@ class LiberoProcessorStep(ObservationProcessorStep):
        return result


+@dataclass
+@ProcessorStepRegistry.register(name="robocasa_processor")
+class RoboCasaProcessorStep(ObservationProcessorStep):
+    """
+    Processes RoboCasa observations into LeRobot format.
+
+    The RoboCasaEnv wrapper returns:
+        - ``pixels.<cam_name>``: (B, C, H, W) float32 images (already converted by vectorenv)
+        - ``observation.robot_state``: (B, 16) float32 proprioception
+
+    This step remaps them to:
+        - ``observation.images.<cam_name>``   (unchanged tensor)
+        - ``observation.state``               (robot_state renamed)
+    """
+
+    def _process_observation(self, observation: dict) -> dict:
+        processed = {}
+        obs_prefix = OBS_PREFIX  # "observation."
+
+        for key, value in observation.items():
+            if key.startswith(f"{OBS_IMAGES}."):
+                # Already in the right place; pass through
+                processed[key] = value
+            elif key == OBS_STATE or key == f"{obs_prefix}robot_state":
+                # Rename robot_state → observation.state
+                processed[OBS_STATE] = value.float() if hasattr(value, "float") else value
+
+        return processed
+
+    def transform_features(
+        self, features: dict[PipelineFeatureType, dict[str, PolicyFeature]]
+    ) -> dict[PipelineFeatureType, dict[str, PolicyFeature]]:
+        return features
+
+    def observation(self, observation: dict) -> dict:
+        return self._process_observation(observation)
+
+
@dataclass
@ProcessorStepRegistry.register(name="isaaclab_arena_processor")
 class IsaaclabArenaProcessorStep(ObservationProcessorStep):
@@ -16,3 +16,5 @@

 from .config_unitree_g1 import UnitreeG1Config
 from .unitree_g1 import UnitreeG1
+
+__all__ = ["UnitreeG1", "UnitreeG1Config"]
@@ -27,11 +27,10 @@ _GAINS: dict[str, dict[str, list[float]]] = {
    },  # pitch, roll, yaw, knee, ankle_pitch, ankle_roll
    "right_leg": {"kp": [150, 150, 150, 300, 40, 40], "kd": [2, 2, 2, 4, 2, 2]},
    "waist": {"kp": [250, 250, 250], "kd": [5, 5, 5]},  # yaw, roll, pitch
-    "left_arm": {"kp": [80, 80, 80, 80], "kd": [3, 3, 3, 3]},  # shoulder_pitch/roll/yaw, elbow
+    "left_arm": {"kp": [50, 50, 80, 80], "kd": [3, 3, 3, 3]},  # shoulder_pitch/roll/yaw, elbow
    "left_wrist": {"kp": [40, 40, 40], "kd": [1.5, 1.5, 1.5]},  # roll, pitch, yaw
-    "right_arm": {"kp": [80, 80, 80, 80], "kd": [3, 3, 3, 3]},
+    "right_arm": {"kp": [50, 50, 80, 80], "kd": [3, 3, 3, 3]},
    "right_wrist": {"kp": [40, 40, 40], "kd": [1.5, 1.5, 1.5]},
-    "other": {"kp": [80, 80, 80, 80, 80, 80], "kd": [3, 3, 3, 3, 3, 3]},
 }


@@ -68,3 +67,7 @@ class UnitreeG1Config(RobotConfig):

    # Compensates for gravity on the unitree's arms using the arm ik solver
    gravity_compensation: bool = False
+
+    # Lower-body controller class name, e.g. "GrootLocomotionController" or
+    # "HolosomaLocomotionController". None disables it.
+    controller: str | None = None
@@ -16,13 +16,11 @@

 import logging
 import os
-import sys
+from collections import deque

 import numpy as np

 logger = logging.getLogger(__name__)
-parent2_dir = os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
-sys.path.append(parent2_dir)


 class WeightedMovingFilter:
@@ -31,18 +29,14 @@ class WeightedMovingFilter:
        self._weights = np.array(weights)
        self._data_size = data_size
        self._filtered_data = np.zeros(self._data_size)
-        self._data_queue = []
+        self._data_queue = deque(maxlen=self._window_size)

    def _apply_filter(self):
        if len(self._data_queue) < self._window_size:
            return self._data_queue[-1]

        data_array = np.array(self._data_queue)
-        temp_filtered_data = np.zeros(self._data_size)
-        for i in range(self._data_size):
-            temp_filtered_data[i] = np.convolve(data_array[:, i], self._weights, mode="valid")[-1]
-
-        return temp_filtered_data
+        return data_array.T @ self._weights

    def add_data(self, new_data):
        assert len(new_data) == self._data_size
@@ -52,9 +46,6 @@ class WeightedMovingFilter:
        ):  # skip duplicate data
            return

-        if len(self._data_queue) >= self._window_size:
-            self._data_queue.pop(0)
-
        self._data_queue.append(new_data)
        self._filtered_data = self._apply_filter()

@@ -71,8 +62,6 @@ class G1_29_ArmIK:  # noqa: N801
        from pinocchio import casadi as cpin

        self._pin = pin
-        np.set_printoptions(precision=5, suppress=True, linewidth=200)
-
        self.unit_test = unit_test

        self.repo_path = snapshot_download("lerobot/unitree-g1-mujoco")
@@ -249,50 +238,35 @@ class G1_29_ArmIK:  # noqa: N801
        self.opti.set_value(self.param_tf_r, right_wrist)
        self.opti.set_value(self.var_q_last, self.init_data)  # for smooth

+        converged = True
        try:
            self.opti.solve()
-
            sol_q = self.opti.value(self.var_q)
-            self.smooth_filter.add_data(sol_q)
-            sol_q = self.smooth_filter.filtered_data
-
-            if current_lr_arm_motor_dq is not None:
-                v = current_lr_arm_motor_dq * 0.0
-            else:
-                v = (sol_q - self.init_data) * 0.0
-
-            self.init_data = sol_q
-
-            sol_tauff = self._pin.rnea(
-                self.reduced_robot.model,
-                self.reduced_robot.data,
-                sol_q,
-                v,
-                np.zeros(self.reduced_robot.model.nv),
-            )
-
-            return sol_q, sol_tauff
-
        except Exception as e:
-            logger.error(f"ERROR in convergence, plotting debug info.{e}")
-
+            converged = False
+            logger.error(f"IK convergence error: {e}")
            sol_q = self.opti.debug.value(self.var_q)
-            self.smooth_filter.add_data(sol_q)
-            sol_q = self.smooth_filter.filtered_data

-            if current_lr_arm_motor_dq is not None:
-                v = current_lr_arm_motor_dq * 0.0
-            else:
-                v = (sol_q - self.init_data) * 0.0
-
-            self.init_data = sol_q
+        self.smooth_filter.add_data(sol_q)
+        sol_q = self.smooth_filter.filtered_data
+        self.init_data = sol_q

+        if not converged:
            logger.error(
                f"sol_q:{sol_q} \nmotorstate: \n{current_lr_arm_motor_q} \nleft_pose: \n{left_wrist} \nright_pose: \n{right_wrist}"
            )
-
            return current_lr_arm_motor_q, np.zeros(self.reduced_robot.model.nv)

+        sol_tauff = self._pin.rnea(
+            self.reduced_robot.model,
+            self.reduced_robot.data,
+            sol_q,
+            np.zeros(self.reduced_robot.model.nv),
+            np.zeros(self.reduced_robot.model.nv),
+        )
+
+        return sol_q, sol_tauff
+
    def solve_tau(self, current_lr_arm_motor_q=None, current_lr_arm_motor_dq=None):
        try:
            q_g1 = np.array(current_lr_arm_motor_q, dtype=float)
@@ -14,12 +14,34 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.

+import importlib
 from enum import IntEnum

+import numpy as np
+
 # ruff: noqa: N801, N815

 NUM_MOTORS = 29

+REMOTE_AXES = ("remote.lx", "remote.ly", "remote.rx", "remote.ry")
+REMOTE_BUTTONS = tuple(f"remote.button.{i}" for i in range(16))
+REMOTE_KEYS = REMOTE_AXES + REMOTE_BUTTONS
+
+
+def default_remote_input() -> dict[str, float]:
+    """Return a zeroed-out remote input dict (axes + buttons)."""
+    return dict.fromkeys(REMOTE_KEYS, 0.0)
+
+
+def get_gravity_orientation(quaternion: list[float] | np.ndarray) -> np.ndarray:
+    """Get gravity orientation from quaternion [w, x, y, z]."""
+    qw, qx, qy, qz = quaternion
+    gravity_orientation = np.zeros(3, dtype=np.float32)
+    gravity_orientation[0] = 2 * (-qz * qx + qw * qy)
+    gravity_orientation[1] = -2 * (qz * qy + qw * qx)
+    gravity_orientation[2] = 1 - 2 * (qw * qw + qz * qz)
+    return gravity_orientation
+

 class G1_29_JointArmIndex(IntEnum):
    # Left arm
@@ -29,7 +51,7 @@ class G1_29_JointArmIndex(IntEnum):
    kLeftElbow = 18
    kLeftWristRoll = 19
    kLeftWristPitch = 20
-    kLeftWristyaw = 21
+    kLeftWristYaw = 21

    # Right arm
    kRightShoulderPitch = 22
@@ -41,6 +63,21 @@ class G1_29_JointArmIndex(IntEnum):
    kRightWristYaw = 28


+def make_locomotion_controller(name: str | None):
+    """Instantiate a locomotion controller by class name. Returns None if name is None."""
+    if name is None:
+        return None
+    controllers = {
+        "GrootLocomotionController": "lerobot.robots.unitree_g1.gr00t_locomotion",
+        "HolosomaLocomotionController": "lerobot.robots.unitree_g1.holosoma_locomotion",
+    }
+    module_path = controllers.get(name)
+    if module_path is None:
+        raise ValueError(f"Unknown controller: {name!r}. Available: {list(controllers)}")
+    module = importlib.import_module(module_path)
+    return getattr(module, name)()
+
+
 class G1_29_JointIndex(IntEnum):
    # Left leg
    kLeftHipPitch = 0
@@ -69,7 +106,7 @@ class G1_29_JointIndex(IntEnum):
    kLeftElbow = 18
    kLeftWristRoll = 19
    kLeftWristPitch = 20
-    kLeftWristyaw = 21
+    kLeftWristYaw = 21

    # Right arm
    kRightShoulderPitch = 22
@@ -14,20 +14,20 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.

-import argparse
 import logging
-import time
 from collections import deque

 import numpy as np
 import onnxruntime as ort
 from huggingface_hub import hf_hub_download

-from lerobot.robots.unitree_g1.config_unitree_g1 import UnitreeG1Config
-from lerobot.robots.unitree_g1.g1_utils import G1_29_JointIndex
-from lerobot.robots.unitree_g1.unitree_g1 import UnitreeG1
+from lerobot.robots.unitree_g1.g1_utils import (
+    REMOTE_AXES,
+    REMOTE_BUTTONS,
+    G1_29_JointIndex,
+    get_gravity_orientation,
+)

-logging.basicConfig(level=logging.INFO)
 logger = logging.getLogger(__name__)


@@ -36,18 +36,13 @@ GROOT_DEFAULT_ANGLES[[0, 6]] = -0.1  # Hip pitch
 GROOT_DEFAULT_ANGLES[[3, 9]] = 0.3  # Knee
 GROOT_DEFAULT_ANGLES[[4, 10]] = -0.2  # Ankle pitch

-MISSING_JOINTS = []
-G1_MODEL = "g1_23"  # Or "g1_29"
-if G1_MODEL == "g1_23":
-    MISSING_JOINTS = [12, 14, 20, 21, 27, 28]  # Waist yaw/pitch, wrist pitch/yaw
-
 # Control parameters
 ACTION_SCALE = 0.25
 CONTROL_DT = 0.02  # 50Hz
 ANG_VEL_SCALE: float = 0.25
 DOF_POS_SCALE: float = 1.0
 DOF_VEL_SCALE: float = 0.05
-CMD_SCALE: list = [2.0, 2.0, 0.25]
+CMD_SCALE: list[float] = [2.0, 2.0, 0.25]


 DEFAULT_GROOT_REPO_ID = "nepyope/GR00T-WholeBodyControl_g1"
@@ -85,11 +80,11 @@ def load_groot_policies(
 class GrootLocomotionController:
    """GR00T lower-body locomotion controller for the Unitree G1."""

-    def __init__(self, policy_balance, policy_walk, robot, config):
-        self.policy_balance = policy_balance
-        self.policy_walk = policy_walk
-        self.robot = robot
-        self.config = config
+    control_dt = CONTROL_DT  # Expose for unitree_g1.py
+
+    def __init__(self):
+        # Load policies
+        self.policy_balance, self.policy_walk = load_groot_policies()

        self.cmd = np.array([0.0, 0.0, 0.0], dtype=np.float32)  # vx, vy, theta_dot

@@ -109,45 +104,60 @@ class GrootLocomotionController:

        logger.info("GrootLocomotionController initialized")

-    def run_step(self):
-        # Get current observation
-        obs = self.robot.get_observation()
+    def reset(self) -> None:
+        """Reset internal state for a new episode."""
+        self.cmd[:] = 0.0
+        self.groot_qj_all[:] = 0.0
+        self.groot_dqj_all[:] = 0.0
+        self.groot_action[:] = 0.0
+        self.groot_obs_single[:] = 0.0
+        self.groot_obs_stacked[:] = 0.0
+        self.groot_height_cmd = 0.74
+        self.groot_orientation_cmd[:] = 0.0
+        self.groot_obs_history.clear()
+        for _ in range(6):
+            self.groot_obs_history.append(np.zeros(86, dtype=np.float32))

-        if not obs:
-            return
+    def run_step(self, action: dict, lowstate) -> dict:
+        """Run one step of the locomotion controller.

-        # Get command from remote controller
-        if obs["remote.buttons"][0]:  # R1 - raise waist
+        Args:
+            action: Action dict containing remote.lx/ly/rx/ry and buttons
+            lowstate: Robot lowstate containing motor positions/velocities and IMU
+
+        Returns:
+            Action dict for lower body joints (0-14)
+        """
+        if lowstate is None:
+            return {}
+
+        buttons = [int(action.get(k, 0)) for k in REMOTE_BUTTONS]
+        if buttons[0]:  # R1 - raise waist
            self.groot_height_cmd += 0.001
            self.groot_height_cmd = np.clip(self.groot_height_cmd, 0.50, 1.00)
-        if obs["remote.buttons"][4]:  # R2 - lower waist
+        if buttons[4]:  # R2 - lower waist
            self.groot_height_cmd -= 0.001
            self.groot_height_cmd = np.clip(self.groot_height_cmd, 0.50, 1.00)

-        self.cmd[0] = obs["remote.ly"]  # Forward/backward
-        self.cmd[1] = obs["remote.lx"] * -1  # Left/right
-        self.cmd[2] = obs["remote.rx"] * -1  # Rotation rate
+        lx, ly, rx, _ry = (action.get(k, 0.0) for k in REMOTE_AXES)
+        self.cmd[0] = ly  # Forward/backward
+        self.cmd[1] = -lx  # Left/right (negated)
+        self.cmd[2] = -rx  # Rotation rate (negated)

-        # Get joint positions and velocities from flat dict
+        # Get joint positions and velocities from lowstate
        for motor in G1_29_JointIndex:
-            name = motor.name
            idx = motor.value
-            self.groot_qj_all[idx] = obs[f"{name}.q"]
-            self.groot_dqj_all[idx] = obs[f"{name}.dq"]
-
-        # Adapt observation for g1_23dof
-        for idx in MISSING_JOINTS:
-            self.groot_qj_all[idx] = 0.0
-            self.groot_dqj_all[idx] = 0.0
+            self.groot_qj_all[idx] = lowstate.motor_state[idx].q
+            self.groot_dqj_all[idx] = lowstate.motor_state[idx].dq

        # Scale joint positions and velocities
        qj_obs = self.groot_qj_all.copy()
        dqj_obs = self.groot_dqj_all.copy()

        # Express IMU data in gravity frame of reference
-        quat = [obs["imu.quat.w"], obs["imu.quat.x"], obs["imu.quat.y"], obs["imu.quat.z"]]
-        ang_vel = np.array([obs["imu.gyro.x"], obs["imu.gyro.y"], obs["imu.gyro.z"]], dtype=np.float32)
-        gravity_orientation = self.robot.get_gravity_orientation(quat)
+        quat = lowstate.imu_state.quaternion
+        ang_vel = np.array(lowstate.imu_state.gyroscope, dtype=np.float32)
+        gravity_orientation = get_gravity_orientation(quat)

        # Scale joint positions and velocities before policy inference
        qj_obs = (qj_obs - GROOT_DEFAULT_ANGLES) * DOF_POS_SCALE
@@ -186,73 +196,10 @@ class GrootLocomotionController:
        # Transform action back to target joint positions
        target_dof_pos_15 = GROOT_DEFAULT_ANGLES[:15] + self.groot_action * ACTION_SCALE

-        # Build action dict (only first 15 joints for GR00T)
+        # Build action dict
        action_dict = {}
        for i in range(15):
            motor_name = G1_29_JointIndex(i).name
            action_dict[f"{motor_name}.q"] = float(target_dof_pos_15[i])

-        # Zero out missing joints for g1_23dof
-        for joint_idx in MISSING_JOINTS:
-            motor_name = G1_29_JointIndex(joint_idx).name
-            action_dict[f"{motor_name}.q"] = 0.0
-
-        # Send action to robot
-        self.robot.send_action(action_dict)
-
-
-def run(repo_id: str = DEFAULT_GROOT_REPO_ID) -> None:
-    """Main function to run the GR00T locomotion controller.
-
-    Args:
-        repo_id: Hugging Face Hub repository ID for GR00T policies.
-    """
-    # Load policies
-    policy_balance, policy_walk = load_groot_policies(repo_id=repo_id)
-
-    # Initialize robot
-    config = UnitreeG1Config()
-    robot = UnitreeG1(config)
-
-    robot.connect()
-
-    # Initialize gr00T locomotion controller
-    groot_controller = GrootLocomotionController(
-        policy_balance=policy_balance,
-        policy_walk=policy_walk,
-        robot=robot,
-        config=config,
-    )
-
-    try:
-        robot.reset(CONTROL_DT, GROOT_DEFAULT_ANGLES)
-
-        logger.info("Use joystick: LY=fwd/back, LX=left/right, RX=rotate, R1=raise waist, R2=lower waist")
-        logger.info("Press Ctrl+C to stop")
-
-        # Run step
-        while not robot._shutdown_event.is_set():
-            start_time = time.time()
-            groot_controller.run_step()
-            elapsed = time.time() - start_time
-            sleep_time = max(0, CONTROL_DT - elapsed)
-            time.sleep(sleep_time)
-    except KeyboardInterrupt:
-        logger.info("Stopping locomotion...")
-    finally:
-        if robot.is_connected:
-            robot.disconnect()
-        logger.info("Done!")
-
-
-if __name__ == "__main__":
-    parser = argparse.ArgumentParser(description="GR00T Locomotion Controller for Unitree G1")
-    parser.add_argument(
-        "--repo-id",
-        type=str,
-        default=DEFAULT_GROOT_REPO_ID,
-        help=f"Hugging Face Hub repo ID for GR00T policies (default: {DEFAULT_GROOT_REPO_ID})",
-    )
-    args = parser.parse_args()
-
-    run(repo_id=args.repo_id)
+        return action_dict
@@ -14,21 +14,21 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.

-import argparse
 import json
 import logging
-import time

 import numpy as np
 import onnx
 import onnxruntime as ort
 from huggingface_hub import hf_hub_download

-from lerobot.robots.unitree_g1.config_unitree_g1 import UnitreeG1Config
-from lerobot.robots.unitree_g1.g1_utils import G1_29_JointIndex
-from lerobot.robots.unitree_g1.unitree_g1 import UnitreeG1
+from lerobot.robots.unitree_g1.g1_utils import (
+    REMOTE_AXES,
+    G1_29_JointArmIndex,
+    G1_29_JointIndex,
+    get_gravity_orientation,
+)

-logging.basicConfig(level=logging.INFO)
 logger = logging.getLogger(__name__)

 DEFAULT_ANGLES = np.zeros(29, dtype=np.float32)
@@ -40,18 +40,13 @@ DEFAULT_ANGLES[16] = 0.2  # Left shoulder roll
 DEFAULT_ANGLES[23] = -0.2  # Right shoulder roll
 DEFAULT_ANGLES[[18, 25]] = 0.6  # Elbow

-MISSING_JOINTS = []
-G1_MODEL = "g1_23"  # Or "g1_29"
-if G1_MODEL == "g1_23":
-    MISSING_JOINTS = [12, 14, 20, 21, 27, 28]  # Waist yaw/pitch, wrist pitch/yaw
-
 # Control parameters
 ACTION_SCALE = 0.25
-CONTROL_DT = 0.02  # 50Hz
+CONTROL_DT = 0.005  # 200Hz
 ANG_VEL_SCALE = 0.25
 DOF_POS_SCALE = 1.0
 DOF_VEL_SCALE = 0.05
-GAIT_PERIOD = 1.0
+GAIT_PERIOD = 0.5


 DEFAULT_HOLOSOMA_REPO_ID = "nepyope/holosoma_locomotion"
@@ -87,7 +82,7 @@ def load_policy(
    logger.info(f"Policy loaded: {policy.get_inputs()[0].shape} → {policy.get_outputs()[0].shape}")

    # Extract KP/KD from ONNX metadata
-    model = onnx.load(policy_path)
+    model = onnx.load(policy_path, load_external_data=False)
    metadata = {prop.key: prop.value for prop in model.metadata_props}

    if "kp" not in metadata or "kd" not in metadata:
@@ -101,15 +96,13 @@ def load_policy(


 class HolosomaLocomotionController:
-    """Holosoma whole-body locomotion controller for Unitree G1."""
+    """Holosoma lower-body locomotion controller for Unitree G1."""

-    def __init__(self, policy, robot, kp: np.ndarray, kd: np.ndarray):
-        self.policy = policy
-        self.robot = robot
+    control_dt = CONTROL_DT  # Expose for unitree_g1.py

-        # Override robot's PD gains with policy gains
-        self.robot.kp = kp
-        self.robot.kd = kd
+    def __init__(self):
+        # Load policy and gains
+        self.policy, self.kp, self.kd = load_policy()

        self.cmd = np.zeros(3, dtype=np.float32)

@@ -124,35 +117,55 @@ class HolosomaLocomotionController:
        self.phase_dt = 2 * np.pi / ((1.0 / CONTROL_DT) * GAIT_PERIOD)
        self.is_standing = True

-    def run_step(self):
-        # Get current observation
-        obs = self.robot.get_observation()
+        logger.info("HolosomaLocomotionController initialized")

-        if not obs:
-            return
+    def reset(self) -> None:
+        """Reset internal state for a new episode."""
+        self.cmd[:] = 0.0
+        self.qj[:] = 0.0
+        self.dqj[:] = 0.0
+        self.obs[:] = 0.0
+        self.last_action[:] = 0.0
+        self.phase = np.array([[0.0, np.pi]], dtype=np.float32)
+        self.is_standing = True

-        # Get command from remote controller
-        ly = obs["remote.ly"] if abs(obs["remote.ly"]) > 0.1 else 0.0
-        lx = obs["remote.lx"] if abs(obs["remote.lx"]) > 0.1 else 0.0
-        rx = obs["remote.rx"] if abs(obs["remote.rx"]) > 0.1 else 0.0
+    def run_step(self, action: dict, lowstate) -> dict:
+        """Run one step of the locomotion controller.
+
+        Args:
+            action: Action dict containing remote.lx/ly/rx/ry
+            lowstate: Robot lowstate containing motor positions/velocities and IMU
+
+        Returns:
+            Action dict for lower body joints (0-14)
+        """
+        if lowstate is None:
+            return {}
+
+        lx, ly, rx, _ry = (action.get(k, 0.0) for k in REMOTE_AXES)
+        ly = ly if abs(ly) > 0.1 else 0.0
+        lx = lx if abs(lx) > 0.1 else 0.0
+        rx = rx if abs(rx) > 0.1 else 0.0
+        ly = np.clip(ly, -0.3, 0.3)
+        lx = np.clip(lx, -0.3, 0.3)
        self.cmd[:] = [ly, -lx, -rx]

-        # Get joint positions and velocities
+        # Get joint positions and velocities from lowstate
        for motor in G1_29_JointIndex:
-            name = motor.name
            idx = motor.value
-            self.qj[idx] = obs[f"{name}.q"]
-            self.dqj[idx] = obs[f"{name}.dq"]
+            self.qj[idx] = lowstate.motor_state[idx].q
+            self.dqj[idx] = lowstate.motor_state[idx].dq

-        # Adapt observation for g1_23dof
-        for idx in MISSING_JOINTS:
-            self.qj[idx] = 0.0
-            self.dqj[idx] = 0.0
+        # Hide arm positions from policy (show DEFAULT_ANGLES instead)
+        # This prevents policy from reacting to teleop arm movements
+        for arm_joint in G1_29_JointArmIndex:
+            self.qj[arm_joint.value] = DEFAULT_ANGLES[arm_joint.value]
+            self.dqj[arm_joint.value] = 0.0

        # Express IMU data in gravity frame of reference
-        quat = [obs["imu.quat.w"], obs["imu.quat.x"], obs["imu.quat.y"], obs["imu.quat.z"]]
-        ang_vel = np.array([obs["imu.gyro.x"], obs["imu.gyro.y"], obs["imu.gyro.z"]], dtype=np.float32)
-        gravity = self.robot.get_gravity_orientation(quat)
+        quat = lowstate.imu_state.quaternion
+        ang_vel = np.array(lowstate.imu_state.gyroscope, dtype=np.float32)
+        gravity = get_gravity_orientation(quat)

        # Scale joint positions and velocities before policy inference
        qj_obs = (self.qj - DEFAULT_ANGLES) * DOF_POS_SCALE
@@ -186,79 +199,16 @@ class HolosomaLocomotionController:
        # Run policy inference
        ort_in = {self.policy.get_inputs()[0].name: self.obs.reshape(1, -1).astype(np.float32)}
        raw_action = self.policy.run(None, ort_in)[0].squeeze()
-        action = np.clip(raw_action, -100.0, 100.0)
-        self.last_action = action.copy()
+        policy_action = np.clip(raw_action, -100.0, 100.0)
+        self.last_action = policy_action.copy()

        # Transform action back to target joint positions
-        target = DEFAULT_ANGLES + action * ACTION_SCALE
+        target = DEFAULT_ANGLES + policy_action * ACTION_SCALE

-        # Build action dict
+        # Build action dict (first 15 joints only)
        action_dict = {}
-        for motor in G1_29_JointIndex:
-            action_dict[f"{motor.name}.q"] = float(target[motor.value])
+        for i in range(15):
+            motor_name = G1_29_JointIndex(i).name
+            action_dict[f"{motor_name}.q"] = float(target[i])

-        # Zero out missing joints for g1_23dof
-        for joint_idx in MISSING_JOINTS:
-            motor_name = G1_29_JointIndex(joint_idx).name
-            action_dict[f"{motor_name}.q"] = 0.0
-
-        # Send action to robot
-        self.robot.send_action(action_dict)
-
-
-def run(repo_id: str = DEFAULT_HOLOSOMA_REPO_ID, policy_type: str = "fastsac") -> None:
-    """Main function to run the Holosoma locomotion controller.
-
-    Args:
-        repo_id: Hugging Face Hub repository ID for Holosoma policies.
-        policy_type: Policy type to use ('fastsac' or 'ppo').
-    """
-    # Load policy and gains
-    policy, kp, kd = load_policy(repo_id=repo_id, policy_type=policy_type)
-
-    # Initialize robot
-    config = UnitreeG1Config()
-    robot = UnitreeG1(config)
-    robot.connect()
-
-    holosoma_controller = HolosomaLocomotionController(policy, robot, kp, kd)
-
-    try:
-        robot.reset(CONTROL_DT, DEFAULT_ANGLES)
-
-        logger.info("Use joystick: LY=fwd/back, LX=left/right, RX=rotate")
-        logger.info("Press Ctrl+C to stop")
-
-        # Run step
-        while not robot._shutdown_event.is_set():
-            start_time = time.time()
-            holosoma_controller.run_step()
-            elapsed = time.time() - start_time
-            sleep_time = max(0, CONTROL_DT - elapsed)
-            time.sleep(sleep_time)
-    except KeyboardInterrupt:
-        logger.info("Stopping locomotion...")
-    finally:
-        if robot.is_connected:
-            robot.disconnect()
-        logger.info("Done!")
-
-
-if __name__ == "__main__":
-    parser = argparse.ArgumentParser(description="Holosoma Locomotion Controller for Unitree G1")
-    parser.add_argument(
-        "--repo-id",
-        type=str,
-        default=DEFAULT_HOLOSOMA_REPO_ID,
-        help=f"Hugging Face Hub repo ID for Holosoma policies (default: {DEFAULT_HOLOSOMA_REPO_ID})",
-    )
-    parser.add_argument(
-        "--policy",
-        type=str,
-        choices=["fastsac", "ppo"],
-        default="fastsac",
-        help="Policy type to use: 'fastsac' (default) or 'ppo'",
-    )
-    args = parser.parse_args()
-
-    run(repo_id=args.repo_id, policy_type=args.policy)
+        return action_dict
@@ -24,6 +24,7 @@ This server runs on the robot and forwards:
 Uses JSON for secure serialization instead of pickle.
 """

+import argparse
 import base64
 import contextlib
 import json
@@ -38,6 +39,8 @@ from unitree_sdk2py.idl.default import unitree_hg_msg_dds__LowCmd_
 from unitree_sdk2py.idl.unitree_hg.msg.dds_ import LowCmd_ as hg_LowCmd, LowState_ as hg_LowState
 from unitree_sdk2py.utils.crc import CRC

+from lerobot.cameras.zmq.image_server import ImageServer
+
 # DDS topic names follow Unitree SDK naming conventions
 # ruff: noqa: N816
 kTopicLowCommand_Debug = "rt/lowcmd"  # action to robot
@@ -150,6 +153,32 @@ def cmd_forward_loop(

 def main() -> None:
    """Main entry point for the robot server bridge."""
+    parser = argparse.ArgumentParser(description="DDS-to-ZMQ bridge server for Unitree G1")
+    parser.add_argument("--camera", action="store_true", help="Also launch camera server")
+    parser.add_argument("--camera-device", type=int, default=4, help="Camera device ID (default: 4)")
+    parser.add_argument("--camera-fps", type=int, default=30, help="Camera FPS (default: 30)")
+    parser.add_argument("--camera-width", type=int, default=640, help="Camera width (default: 640)")
+    parser.add_argument("--camera-height", type=int, default=480, help="Camera height (default: 480)")
+    parser.add_argument("--camera-port", type=int, default=5555, help="Camera ZMQ port (default: 5555)")
+    args = parser.parse_args()
+
+    # Optionally start camera server in background thread
+    camera_thread = None
+    if args.camera:
+        camera_config = {
+            "fps": args.camera_fps,
+            "cameras": {
+                "head_camera": {
+                    "device_id": args.camera_device,
+                    "shape": [args.camera_height, args.camera_width],
+                }
+            },
+        }
+        camera_server = ImageServer(camera_config, port=args.camera_port)
+        camera_thread = threading.Thread(target=camera_server.run, daemon=True)
+        camera_thread.start()
+        print(f"Camera server started on port {args.camera_port} (device {args.camera_device})")
+
    # initialize DDS
    ChannelFactoryInitialize(0)

@@ -206,6 +235,8 @@ def main() -> None:
        shutdown_event.set()
        ctx.term()  # terminates blocking zmq.recv() calls
        t_state.join(timeout=2.0)
+        if camera_thread is not None:
+            camera_thread.join(timeout=2.0)


 if __name__ == "__main__":
@@ -14,27 +14,67 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.

+from __future__ import annotations
+
 import logging
-import struct
 import threading
 import time
 from dataclasses import dataclass, field
 from functools import cached_property
-from typing import Any
+from typing import TYPE_CHECKING, Protocol, runtime_checkable

 import numpy as np

 from lerobot.cameras.utils import make_cameras_from_configs
 from lerobot.envs.factory import make_env
 from lerobot.processor import RobotAction, RobotObservation
-from lerobot.robots.unitree_g1.g1_utils import G1_29_JointArmIndex, G1_29_JointIndex
-from lerobot.robots.unitree_g1.robot_kinematic_processor import G1_29_ArmIK
+from lerobot.robots.unitree_g1.g1_kinematics import G1_29_ArmIK
+from lerobot.robots.unitree_g1.g1_utils import (
+    REMOTE_AXES,
+    REMOTE_KEYS,
+    G1_29_JointArmIndex,
+    G1_29_JointIndex,
+    default_remote_input,
+    make_locomotion_controller,
+)
+from lerobot.utils.import_utils import _unitree_sdk_available

 from ..robot import Robot
 from .config_unitree_g1 import UnitreeG1Config

+if TYPE_CHECKING or _unitree_sdk_available:
+    from unitree_sdk2py.core.channel import (
+        ChannelFactoryInitialize as _SDKChannelFactoryInitialize,
+        ChannelPublisher as _SDKChannelPublisher,
+        ChannelSubscriber as _SDKChannelSubscriber,
+    )
+    from unitree_sdk2py.idl.default import unitree_hg_msg_dds__LowCmd_
+    from unitree_sdk2py.idl.unitree_hg.msg.dds_ import (
+        LowCmd_ as hg_LowCmd,
+        LowState_ as hg_LowState,
+    )
+    from unitree_sdk2py.utils.crc import CRC
+else:
+    _SDKChannelFactoryInitialize = None
+    _SDKChannelPublisher = None
+    _SDKChannelSubscriber = None
+    unitree_hg_msg_dds__LowCmd_ = None
+    hg_LowCmd = None
+    hg_LowState = None
+    CRC = None
+
 logger = logging.getLogger(__name__)

+
+@runtime_checkable
+class LocomotionController(Protocol):
+    control_dt: float
+
+    def run_step(self, action: dict, lowstate) -> dict: ...
+
+    def reset(self) -> None: ...
+
+
 # DDS topic names follow Unitree SDK naming conventions
 # ruff: noqa: N816
 kTopicLowCommand_Debug = "rt/lowcmd"
@@ -63,7 +103,7 @@ class IMUState:
 class G1_29_LowState:  # noqa: N801
    motor_state: list[MotorState] = field(default_factory=lambda: [MotorState() for _ in G1_29_JointIndex])
    imu_state: IMUState = field(default_factory=IMUState)
-    wireless_remote: Any = None  # Raw wireless remote data
+    wireless_remote: bytes | None = None  # Raw wireless remote data
    mode_machine: int = 0  # Robot mode


@@ -71,25 +111,6 @@ class UnitreeG1(Robot):
    config_class = UnitreeG1Config
    name = "unitree_g1"

-    # unitree remote controller
-    class RemoteController:
-        def __init__(self):
-            self.lx = 0
-            self.ly = 0
-            self.rx = 0
-            self.ry = 0
-            self.button = [0] * 16
-
-        def set(self, data):
-            # wireless_remote
-            keys = struct.unpack("H", data[2:4])[0]
-            for i in range(16):
-                self.button[i] = (keys & (1 << i)) >> i
-            self.lx = struct.unpack("f", data[4:8])[0]
-            self.rx = struct.unpack("f", data[8:12])[0]
-            self.ry = struct.unpack("f", data[12:16])[0]
-            self.ly = struct.unpack("f", data[20:24])[0]
-
    def __init__(self, config: UnitreeG1Config):
        super().__init__(config)

@@ -103,11 +124,9 @@ class UnitreeG1(Robot):

        # Import channel classes based on mode
        if config.is_simulation:
-            from unitree_sdk2py.core.channel import (
-                ChannelFactoryInitialize,
-                ChannelPublisher,
-                ChannelSubscriber,
-            )
+            self._ChannelFactoryInitialize = _SDKChannelFactoryInitialize
+            self._ChannelPublisher = _SDKChannelPublisher
+            self._ChannelSubscriber = _SDKChannelSubscriber
        else:
            from lerobot.robots.unitree_g1.unitree_sdk2_socket import (
                ChannelFactoryInitialize,
@@ -115,22 +134,30 @@ class UnitreeG1(Robot):
                ChannelSubscriber,
            )

-        # Store for use in connect()
-        self._ChannelFactoryInitialize = ChannelFactoryInitialize
-        self._ChannelPublisher = ChannelPublisher
-        self._ChannelSubscriber = ChannelSubscriber
+            self._ChannelFactoryInitialize = ChannelFactoryInitialize
+            self._ChannelPublisher = ChannelPublisher
+            self._ChannelSubscriber = ChannelSubscriber

        # Initialize state variables
        self.sim_env = None
        self._env_wrapper = None
        self._lowstate = None
+        self._lowstate_lock = threading.Lock()
        self._shutdown_event = threading.Event()
        self.subscribe_thread = None
-        self.remote_controller = self.RemoteController()

-        self.arm_ik = G1_29_ArmIK()
+        self.arm_ik = G1_29_ArmIK() if config.gravity_compensation else None

-    def _subscribe_motor_state(self):  # polls robot state @ 250Hz
+        # Lower-body controller loaded dynamically
+        self.controller: LocomotionController | None = make_locomotion_controller(config.controller)
+
+        # Controller thread state
+        self._controller_thread = None
+        self._controller_action_lock = threading.Lock()
+        self.controller_input = default_remote_input()
+        self.controller_output = {}
+
+    def _subscribe_lowstate(self):  # polls robot state @ 250Hz
        while not self._shutdown_event.is_set():
            start_time = time.time()

@@ -143,11 +170,11 @@ class UnitreeG1(Robot):
                lowstate = G1_29_LowState()

                # Capture motor states using jointindex
-                for id in G1_29_JointIndex:
-                    lowstate.motor_state[id].q = msg.motor_state[id].q
-                    lowstate.motor_state[id].dq = msg.motor_state[id].dq
-                    lowstate.motor_state[id].tau_est = msg.motor_state[id].tau_est
-                    lowstate.motor_state[id].temperature = msg.motor_state[id].temperature
+                for joint in G1_29_JointIndex:
+                    lowstate.motor_state[joint].q = msg.motor_state[joint].q
+                    lowstate.motor_state[joint].dq = msg.motor_state[joint].dq
+                    lowstate.motor_state[joint].tau_est = msg.motor_state[joint].tau_est
+                    lowstate.motor_state[joint].temperature = msg.motor_state[joint].temperature

                # Capture IMU state
                lowstate.imu_state.quaternion = list(msg.imu_state.quaternion)
@@ -162,31 +189,106 @@ class UnitreeG1(Robot):
                # Capture mode_machine
                lowstate.mode_machine = msg.mode_machine

-                self._lowstate = lowstate
+                with self._lowstate_lock:
+                    self._lowstate = lowstate

            current_time = time.time()
            all_t_elapsed = current_time - start_time
            sleep_time = max(0, (self.control_dt - all_t_elapsed))  # maintain constant control dt
            time.sleep(sleep_time)

+    def publish_lowcmd(
+        self,
+        action: RobotAction,
+        kp: np.ndarray | list[float] | None = None,
+        kd: np.ndarray | list[float] | None = None,
+        tau: np.ndarray | list[float] | None = None,
+    ) -> None:  # writes robot command whenever requested
+        for motor in G1_29_JointIndex:
+            key = f"{motor.name}.q"
+            if key in action:
+                self.msg.motor_cmd[motor.value].q = action[key]
+                self.msg.motor_cmd[motor.value].qd = 0
+                self.msg.motor_cmd[motor.value].kp = (
+                    kp[motor.value] if kp is not None else self.kp[motor.value]
+                )
+                self.msg.motor_cmd[motor.value].kd = (
+                    kd[motor.value] if kd is not None else self.kd[motor.value]
+                )
+                self.msg.motor_cmd[motor.value].tau = tau[motor.value] if tau is not None else 0.0
+
+        self.msg.crc = self.crc.Crc(self.msg)
+        self.lowcmd_publisher.Write(self.msg)
+
+    @property
+    def _cameras_ft(self) -> dict[str, tuple]:
+        return {
+            cam: (self.config.cameras[cam].height, self.config.cameras[cam].width, 3) for cam in self.cameras
+        }
+
+    @cached_property
+    def observation_features(self) -> dict[str, type | tuple]:
+        return {**self._motors_ft, **self._cameras_ft}
+
    @cached_property
    def action_features(self) -> dict[str, type]:
-        return {f"{G1_29_JointIndex(motor).name}.q": float for motor in G1_29_JointIndex}
+        if self.controller is None:
+            return {f"{G1_29_JointIndex(motor).name}.q": float for motor in G1_29_JointIndex}

-    def calibrate(self) -> None:  # robot is already calibrated
+        arm_features = {f"{G1_29_JointArmIndex(motor).name}.q": float for motor in G1_29_JointArmIndex}
+        remote_features = dict.fromkeys(REMOTE_AXES, float)
+        return {**arm_features, **remote_features}
+
+    def _controller_loop(self):
+        """Background thread that runs controller at policy's control_dt."""
+        control_dt = self.controller.control_dt
+        logger.info(f"Controller loop starting with control_dt={control_dt} ({1.0 / control_dt:.1f}Hz)")
+
+        loop_count = 0
+        last_log_time = time.time()
+
+        while not self._shutdown_event.is_set():
+            start_time = time.time()
+
+            with self._lowstate_lock:
+                lowstate = self._lowstate
+
+            if lowstate is not None and self.controller is not None:
+                loop_count += 1
+                if time.time() - last_log_time >= 5.0:  # Log every 5 seconds
+                    actual_hz = loop_count / (time.time() - last_log_time)
+                    logger.info(
+                        f"Controller actual rate: {actual_hz:.1f}Hz (target: {1.0 / control_dt:.1f}Hz)"
+                    )
+                    loop_count = 0
+                    last_log_time = time.time()
+                # Read controller input snapshot
+                with self._controller_action_lock:
+                    controller_input = dict(self.controller_input)
+
+                # Run controller step
+                controller_action = self.controller.run_step(controller_input, lowstate)
+
+                # Write controller output snapshot
+                with self._controller_action_lock:
+                    self.controller_output = dict(controller_action)
+
+                ctrl_kp = self.controller.kp if hasattr(self.controller, "kp") else None
+                ctrl_kd = self.controller.kd if hasattr(self.controller, "kd") else None
+                self.publish_lowcmd(controller_action, kp=ctrl_kp, kd=ctrl_kd)
+
+            elapsed = time.time() - start_time
+            sleep_time = max(0, control_dt - elapsed)
+            time.sleep(sleep_time)
+
+    def calibrate(self) -> None:
+        # TODO: implement g1_29 calibration
        pass

    def configure(self) -> None:
        pass

    def connect(self, calibrate: bool = True) -> None:  # connect to DDS
-        from unitree_sdk2py.idl.default import unitree_hg_msg_dds__LowCmd_
-        from unitree_sdk2py.idl.unitree_hg.msg.dds_ import (
-            LowCmd_ as hg_LowCmd,
-            LowState_ as hg_LowState,
-        )
-        from unitree_sdk2py.utils.crc import CRC
-
        # Initialize DDS channel and simulation environment
        if self.config.is_simulation:
            self._ChannelFactoryInitialize(0, "lo")
@@ -194,7 +296,7 @@ class UnitreeG1(Robot):
            # Extract the actual gym env from the dict structure
            self.sim_env = self._env_wrapper["hub_env"][0].envs[0]
        else:
-            self._ChannelFactoryInitialize(0)
+            self._ChannelFactoryInitialize(0, config=self.config)

        # Initialize direct motor control interface
        self.lowcmd_publisher = self._ChannelPublisher(kTopicLowCommand_Debug, hg_LowCmd)
@@ -203,7 +305,7 @@ class UnitreeG1(Robot):
        self.lowstate_subscriber.Init()

        # Start subscribe thread to read robot state
-        self.subscribe_thread = threading.Thread(target=self._subscribe_motor_state)
+        self.subscribe_thread = threading.Thread(target=self._subscribe_lowstate)
        self.subscribe_thread.start()

        # Connect cameras
@@ -220,25 +322,53 @@ class UnitreeG1(Robot):

        # Wait for first state message to arrive
        lowstate = None
+        deadline = time.time() + 10.0
        while lowstate is None:
-            lowstate = self._lowstate
+            with self._lowstate_lock:
+                lowstate = self._lowstate
            if lowstate is None:
+                if time.time() > deadline:
+                    raise TimeoutError("Timed out waiting for robot state (10s)")
+                logger.warning("[UnitreeG1] Waiting for robot state...")
                time.sleep(0.01)
-            logger.warning("[UnitreeG1] Waiting for robot state...")
-        logger.warning("[UnitreeG1] Connected to robot.")
+        logger.info("[UnitreeG1] Connected to robot.")
        self.msg.mode_machine = lowstate.mode_machine

-        # Initialize all motors with unified kp/kd from config
        self.kp = np.array(self.config.kp, dtype=np.float32)
        self.kd = np.array(self.config.kd, dtype=np.float32)

-        for id in G1_29_JointIndex:
-            self.msg.motor_cmd[id].mode = 1
-            self.msg.motor_cmd[id].kp = self.kp[id.value]
-            self.msg.motor_cmd[id].kd = self.kd[id.value]
-            self.msg.motor_cmd[id].q = lowstate.motor_state[id.value].q
+        for joint in G1_29_JointIndex:
+            self.msg.motor_cmd[joint].mode = 1
+            self.msg.motor_cmd[joint].kp = self.kp[joint.value]
+            self.msg.motor_cmd[joint].kd = self.kd[joint.value]
+            self.msg.motor_cmd[joint].q = lowstate.motor_state[joint.value].q
+
+        # Start controller thread if enabled
+        if self.controller is not None:
+            self._controller_thread = threading.Thread(target=self._controller_loop, daemon=True)
+            self._controller_thread.start()
+            fps = int(1.0 / self.controller.control_dt)
+            logger.info(f"Controller thread started ({fps}Hz)")
+
+    def _send_zero_torque(self) -> None:
+        """Send a zero-gain command to make joints passive before shutting down."""
+        try:
+            with self._lowstate_lock:
+                lowstate = self._lowstate
+            if lowstate is None:
+                return
+            action = {f"{motor.name}.q": lowstate.motor_state[motor.value].q for motor in G1_29_JointIndex}
+            zero_gains = np.zeros(29, dtype=np.float32)
+            self.publish_lowcmd(action, kp=zero_gains, kd=zero_gains, tau=zero_gains)
+            logger.info("Sent zero-torque command for safe shutdown")
+        except Exception as e:
+            logger.warning(f"Failed to send zero-torque on disconnect: {e}")

    def disconnect(self):
+        # Put robot in passive mode before stopping threads
+        if not self.config.is_simulation:
+            self._send_zero_torque()
+
        # Signal thread to stop and unblock any waits
        self._shutdown_event.set()

@@ -248,6 +378,12 @@ class UnitreeG1(Robot):
            if self.subscribe_thread.is_alive():
                logger.warning("Subscribe thread did not stop cleanly")

+        # Wait for controller thread to finish
+        if self._controller_thread is not None:
+            self._controller_thread.join(timeout=2.0)
+            if self._controller_thread.is_alive():
+                logger.warning("Controller thread did not stop cleanly")
+
        # Close simulation environment
        if self.config.is_simulation and self.sim_env is not None:
            try:
@@ -274,7 +410,8 @@ class UnitreeG1(Robot):
            cam.disconnect()

    def get_observation(self) -> RobotObservation:
-        lowstate = self._lowstate
+        with self._lowstate_lock:
+            lowstate = self._lowstate
        if lowstate is None:
            return {}

@@ -313,14 +450,9 @@ class UnitreeG1(Robot):
            obs["imu.rpy.pitch"] = lowstate.imu_state.rpy[1]
            obs["imu.rpy.yaw"] = lowstate.imu_state.rpy[2]

-        # Controller - parse wireless_remote and add to obs
-        if lowstate.wireless_remote and len(lowstate.wireless_remote) >= 24:
-            self.remote_controller.set(lowstate.wireless_remote)
-        obs["remote.buttons"] = self.remote_controller.button.copy()
-        obs["remote.lx"] = self.remote_controller.lx
-        obs["remote.ly"] = self.remote_controller.ly
-        obs["remote.rx"] = self.remote_controller.rx
-        obs["remote.ry"] = self.remote_controller.ry
+        # Wireless remote (raw bytes for teleoperator)
+        if lowstate.wireless_remote:
+            obs["wireless_remote"] = lowstate.wireless_remote

        # Cameras - read images from ZMQ cameras
        for cam_name, cam in self._cameras.items():
@@ -328,73 +460,63 @@ class UnitreeG1(Robot):

        return obs

+    def send_action(self, action: RobotAction) -> RobotAction:
+        action_to_publish = action
+        if self.controller is not None:
+            # Controller thread owns legs/waist. Here we only update joystick inputs
+            # and publish arm targets from the teleoperator.
+            self._update_controller_action(action)
+            arm_prefixes = tuple(j.name for j in G1_29_JointArmIndex)
+            action_to_publish = {
+                key: value
+                for key, value in action.items()
+                if key.endswith(".q") and key.startswith(arm_prefixes)
+            }
+
+        tau = None
+        if self.config.gravity_compensation and self.arm_ik is not None:
+            tau = np.zeros(29, dtype=np.float32)
+            action_np = np.array(
+                [
+                    action_to_publish.get(f"{joint.name}.q", self.msg.motor_cmd[joint.value].q)
+                    for joint in G1_29_JointArmIndex
+                ],
+                dtype=np.float32,
+            )
+            arm_tau = self.arm_ik.solve_tau(action_np)
+            arm_start_idx = G1_29_JointArmIndex.kLeftShoulderPitch.value
+            for joint in G1_29_JointArmIndex:
+                local_idx = joint.value - arm_start_idx
+                tau[joint.value] = arm_tau[local_idx]
+
+        self.publish_lowcmd(action_to_publish, tau=tau)
+        return action
+
+    def _update_controller_action(self, action: RobotAction) -> None:
+        """Update controller input state from incoming teleop action."""
+        with self._controller_action_lock:
+            for key in REMOTE_KEYS:
+                if key in action:
+                    self.controller_input[key] = action[key]
+
    @property
    def is_calibrated(self) -> bool:
        return True

    @property
    def is_connected(self) -> bool:
-        return self._lowstate is not None
+        with self._lowstate_lock:
+            return self._lowstate is not None

    @property
    def _motors_ft(self) -> dict[str, type]:
+        """Joint positions for all 29 joints."""
        return {f"{G1_29_JointIndex(motor).name}.q": float for motor in G1_29_JointIndex}

    @property
    def cameras(self) -> dict:
        return self._cameras

-    @property
-    def _cameras_ft(self) -> dict[str, tuple]:
-        return {
-            cam: (self.config.cameras[cam].height, self.config.cameras[cam].width, 3) for cam in self.cameras
-        }
-
-    @cached_property
-    def observation_features(self) -> dict[str, type | tuple]:
-        return {**self._motors_ft, **self._cameras_ft}
-
-    def send_action(self, action: RobotAction) -> RobotAction:
-        for motor in G1_29_JointIndex:
-            key = f"{motor.name}.q"
-            if key in action:
-                self.msg.motor_cmd[motor.value].q = action[key]
-                self.msg.motor_cmd[motor.value].qd = 0
-                self.msg.motor_cmd[motor.value].kp = self.kp[motor.value]
-                self.msg.motor_cmd[motor.value].kd = self.kd[motor.value]
-                self.msg.motor_cmd[motor.value].tau = 0
-
-        if self.config.gravity_compensation:
-            # Build action_np from motor commands (arm joints are indices 15-28, local indices 0-13)
-            action_np = np.zeros(14)
-            arm_start_idx = G1_29_JointArmIndex.kLeftShoulderPitch.value  # 15
-            for joint in G1_29_JointArmIndex:
-                local_idx = joint.value - arm_start_idx
-                action_np[local_idx] = self.msg.motor_cmd[joint.value].q
-            tau = self.arm_ik.solve_tau(action_np)
-
-            # Apply tau back to motor commands
-            for joint in G1_29_JointArmIndex:
-                local_idx = joint.value - arm_start_idx
-                self.msg.motor_cmd[joint.value].tau = tau[local_idx]
-
-        self.msg.crc = self.crc.Crc(self.msg)
-        self.lowcmd_publisher.Write(self.msg)
-        return action
-
-    def get_gravity_orientation(self, quaternion):  # get gravity orientation from quaternion
-        """Get gravity orientation from quaternion."""
-        qw = quaternion[0]
-        qx = quaternion[1]
-        qy = quaternion[2]
-        qz = quaternion[3]
-
-        gravity_orientation = np.zeros(3)
-        gravity_orientation[0] = 2 * (-qz * qx + qw * qy)
-        gravity_orientation[1] = -2 * (qz * qy + qw * qx)
-        gravity_orientation[2] = 1 - 2 * (qw * qw + qz * qz)
-        return gravity_orientation
-
    def reset(
        self,
        control_dt: float | None = None,
@@ -407,15 +529,9 @@ class UnitreeG1(Robot):

        if self.config.is_simulation and self.sim_env is not None:
            self.sim_env.reset()
-
-            for motor in G1_29_JointIndex:
-                self.msg.motor_cmd[motor.value].q = default_positions[motor.value]
-                self.msg.motor_cmd[motor.value].qd = 0
-                self.msg.motor_cmd[motor.value].kp = self.kp[motor.value]
-                self.msg.motor_cmd[motor.value].kd = self.kd[motor.value]
-                self.msg.motor_cmd[motor.value].tau = 0
-            self.msg.crc = self.crc.Crc(self.msg)
-            self.lowcmd_publisher.Write(self.msg)
+            self.publish_lowcmd(
+                {f"{motor.name}.q": float(default_positions[motor.value]) for motor in G1_29_JointIndex}
+            )
        else:
            total_time = 3.0
            num_steps = int(total_time / control_dt)
@@ -446,4 +562,8 @@ class UnitreeG1(Robot):
                sleep_time = max(0, control_dt - elapsed)
                time.sleep(sleep_time)

+        # Reset controller internal state (gait phase, obs history, etc.)
+        if self.controller is not None and hasattr(self.controller, "reset"):
+            self.controller.reset()
+
        logger.info("Reached default position")
@@ -22,6 +22,8 @@ import zmq

 from lerobot.robots.unitree_g1.config_unitree_g1 import UnitreeG1Config

+# Module-level ZMQ state mirrors the Unitree SDK's global ChannelFactory Singleton.
+# Only one robot connection per process is supported.
 _ctx: zmq.Context | None = None
 _lowcmd_sock: zmq.Socket | None = None
 _lowstate_sock: zmq.Socket | None = None
@@ -97,17 +99,22 @@ def lowcmd_to_dict(topic: str, msg: Any) -> dict[str, Any]:
    }


-def ChannelFactoryInitialize(*args: Any, **kwargs: Any) -> None:  # noqa: N802
+def ChannelFactoryInitialize(domain_id: int = 0, config: Any = None) -> None:  # noqa: N802
    """
    Initialize ZMQ sockets for robot communication.

    This function mimics the Unitree SDK's ChannelFactoryInitialize but uses
    ZMQ sockets to connect to the robot server bridge instead of DDS.
+
+    Args:
+        domain_id: Ignored (for API compatibility with Unitree SDK)
+        config: UnitreeG1Config instance with robot_ip
    """
    global _ctx, _lowcmd_sock, _lowstate_sock

    # read socket config
-    config = UnitreeG1Config()
+    if config is None:
+        config = UnitreeG1Config()
    robot_ip = config.robot_ip

    ctx = zmq.Context.instance()
@@ -369,6 +369,8 @@ def record_loop(
            act_processed_policy: RobotAction = make_robot_action(action_values, dataset.features)

        elif policy is None and isinstance(teleop, Teleoperator):
+            if robot.name == "unitree_g1":
+                teleop.send_feedback(obs)
            act = teleop.get_action()

            # Applies a pipeline to the raw teleop action, default is IdentityProcessor
@@ -556,10 +558,6 @@ def record(cfg: RecordConfig) -> LeRobotDataset:
                ):
                    log_say("Reset the environment", cfg.play_sounds)

-                    # reset g1 robot
-                    if robot.name == "unitree_g1":
-                        robot.reset()
-
                    record_loop(
                        robot=robot,
                        events=events,
@@ -60,6 +60,7 @@ import rerun as rr

 from lerobot.cameras.opencv.configuration_opencv import OpenCVCameraConfig  # noqa: F401
 from lerobot.cameras.realsense.configuration_realsense import RealSenseCameraConfig  # noqa: F401
+from lerobot.cameras.zmq.configuration_zmq import ZMQCameraConfig  # noqa: F401
 from lerobot.configs import parser
 from lerobot.processor import (
    RobotAction,
@@ -153,7 +154,6 @@ def teleop_loop(

    display_len = max(len(key) for key in robot.action_features)
    start = time.perf_counter()
-
    while True:
        loop_start = time.perf_counter()

@@ -163,6 +163,9 @@ def teleop_loop(
        # given that it is the identity processor as default
        obs = robot.get_observation()

+        if robot.name == "unitree_g1":
+            teleop.send_feedback(obs)
+
        # Get teleop action
        raw_action = teleop.get_action()

@@ -209,7 +209,11 @@ def train(cfg: TrainPipelineConfig, accelerator: Accelerator | None = None):

    # Use accelerator's device
    device = accelerator.device
-    torch.backends.cudnn.benchmark = True
+    if cfg.cudnn_deterministic:
+        torch.backends.cudnn.deterministic = True
+        torch.backends.cudnn.benchmark = False
+    else:
+        torch.backends.cudnn.benchmark = True
    torch.backends.cuda.matmul.allow_tf32 = True

    # Dataset loading synchronization: main process downloads first to avoid race conditions
@@ -19,3 +19,13 @@ from .exo_calib import ExoskeletonCalibration, ExoskeletonJointCalibration
 from .exo_ik import ExoskeletonIKHelper
 from .exo_serial import ExoskeletonArm
 from .unitree_g1 import UnitreeG1Teleoperator
+
+__all__ = [
+    "ExoskeletonArmPortConfig",
+    "ExoskeletonCalibration",
+    "ExoskeletonIKHelper",
+    "ExoskeletonJointCalibration",
+    "ExoskeletonArm",
+    "UnitreeG1Teleoperator",
+    "UnitreeG1TeleoperatorConfig",
+]
@@ -35,6 +35,9 @@ import serial
 logger = logging.getLogger(__name__)


+ADC_MAX = 2**12 - 1
+ADC_HALF = ADC_MAX / 2
+
 # exoskeleton joint names -> ADC channel pairs. TODO: add wrist pitch and wrist yaw
 JOINTS = {
    "shoulder_pitch": (0, 1),
@@ -59,7 +62,7 @@ class ExoskeletonCalibration:

    version: int = 2
    side: str = ""
-    adc_max: int = 2**12 - 1
+    adc_max: int = ADC_MAX
    joints: list[ExoskeletonJointCalibration] = field(default_factory=list)

    def to_dict(self) -> dict:
@@ -92,7 +95,7 @@ class ExoskeletonCalibration:
        return cls(
            version=data.get("version", 2),
            side=data.get("side", ""),
-            adc_max=data.get("adc_max", 2**12 - 1),
+            adc_max=data.get("adc_max", ADC_MAX),
            joints=joints,
        )

@@ -112,11 +115,8 @@ class CalibParams:


 def normalize_angle(angle: float) -> float:
-    while angle > np.pi:
-        angle -= 2 * np.pi
-    while angle < -np.pi:
-        angle += 2 * np.pi
-    return angle
+    """Normalize angle to [-pi, pi]."""
+    return float(np.arctan2(np.sin(angle), np.cos(angle)))


 def joint_z_and_angle(raw16: list[int], j: ExoskeletonJointCalibration) -> tuple[np.ndarray, float]:
@@ -125,7 +125,7 @@ def joint_z_and_angle(raw16: list[int], j: ExoskeletonJointCalibration) -> tuple
    """
    pair = JOINTS[j.name]
    s, c = raw16[pair[0]], raw16[pair[1]]  # get sin and cos
-    p = np.array([float(c) - (2**12 - 1) / 2, float(s) - (2**12 - 1) / 2])  # center the raw values
+    p = np.array([float(c) - ADC_HALF, float(s) - ADC_HALF])  # center the raw values
    z = np.asarray(j.T) @ (
        p - np.asarray(j.center_fit)
    )  # center the ellipse and invert the transformation matrix to get unit circle coords
@@ -167,7 +167,7 @@ def run_exo_calibration(

    def read_joint_point(raw16: list[int], pair: tuple[int, int]):
        s, c = raw16[pair[0]], raw16[pair[1]]
-        return float(c) - (2**12 - 1) / 2, float(s) - (2**12 - 1) / 2, float(s), float(c)
+        return float(c) - ADC_HALF, float(s) - ADC_HALF, float(s), float(c)

    def select_fit_subset(xs, ys):
        """Select and filter points for ellipse fitting. Trims outliers by radius and downsamples."""
@@ -317,7 +317,7 @@ def run_exo_calibration(
                        calib = ExoskeletonCalibration(
                            version=2,
                            side=side,
-                            adc_max=2**12 - 1,
+                            adc_max=ADC_MAX,
                            joints=[
                                ExoskeletonJointCalibration(
                                    name=j["name"],
@@ -367,8 +367,8 @@ def run_exo_calibration(
                    state["win_s"].append(s_raw)
                    state["win_c"].append(c_raw)
                    if len(state["win_s"]) >= max(3, params.median_window):
-                        state["ys"].append(running_median(state["win_s"]) - (2**12 - 1) / 2)
-                        state["xs"].append(running_median(state["win_c"]) - (2**12 - 1) / 2)
+                        state["ys"].append(running_median(state["win_s"]) - ADC_HALF)
+                        state["xs"].append(running_median(state["win_c"]) - ADC_HALF)
                else:
                    jdata = joints_out[-1]
                    z = np.array(jdata["T"]) @ (np.array([x_raw, y_raw]) - np.array(jdata["center_fit"]))
@@ -25,8 +25,8 @@ from dataclasses import dataclass

 import numpy as np

+from lerobot.robots.unitree_g1.g1_kinematics import G1_29_ArmIK
 from lerobot.robots.unitree_g1.g1_utils import G1_29_JointArmIndex
-from lerobot.robots.unitree_g1.robot_kinematic_processor import G1_29_ArmIK

 from .exo_calib import JOINTS

@@ -32,25 +32,29 @@ def parse_raw16(line: bytes) -> list[int] | None:
        if len(parts) < 16:
            return None
        return [int(x) for x in parts[:16]]
-    except Exception:
+    except (ValueError, IndexError):
        return None


 def read_raw_from_serial(ser) -> list[int] | None:
    """Read latest sample from serial; if buffer is backed up, keep only the newest."""
-    last = None
-    while ser.in_waiting > 0:
-        b = ser.readline()
-        if not b:
-            break
-        raw16 = parse_raw16(b)
-        if raw16 is not None:
-            last = raw16
-    if last is None:
-        b = ser.readline()
-        if b:
-            last = parse_raw16(b)
-    return last
+    try:
+        last = None
+        while ser.in_waiting > 0:
+            b = ser.readline()
+            if not b:
+                break
+            raw16 = parse_raw16(b)
+            if raw16 is not None:
+                last = raw16
+        if last is None:
+            b = ser.readline()
+            if b:
+                last = parse_raw16(b)
+        return last
+    except serial.SerialException as e:
+        logger.warning(f"Serial read error: {e}")
+        return None


@dataclass
@@ -115,5 +119,6 @@ class ExoskeletonArm:
        return {} if raw is None else exo_raw_to_angles(raw, self.calibration)

    def calibrate(self) -> None:
-        ser = self._ser
-        self.calibration = run_exo_calibration(ser, self.side, self.calibration_fpath)
+        if not self.is_connected:
+            raise RuntimeError("Cannot calibrate: exoskeleton not connected")
+        self.calibration = run_exo_calibration(self._ser, self.side, self.calibration_fpath)
@@ -17,9 +17,22 @@
 import logging
 import time
 from functools import cached_property
+from typing import TYPE_CHECKING, Any

-from lerobot.robots.unitree_g1.g1_utils import G1_29_JointIndex
+from lerobot.robots.unitree_g1.g1_utils import REMOTE_AXES, G1_29_JointArmIndex
 from lerobot.utils.constants import HF_LEROBOT_CALIBRATION, TELEOPERATORS
+from lerobot.utils.import_utils import _unitree_sdk_available
+
+if TYPE_CHECKING or _unitree_sdk_available:
+    from unitree_sdk2py.utils.joystick import Joystick
+else:
+
+    class Joystick:
+        def __init__(self):
+            raise ImportError(
+                "unitree_sdk2py is required for RemoteController. Install with: pip install unitree_sdk2py"
+            )
+

 from ..teleoperator import Teleoperator
 from .config_unitree_g1 import UnitreeG1TeleoperatorConfig
@@ -29,6 +42,120 @@ from .exo_serial import ExoskeletonArm
 logger = logging.getLogger(__name__)


+class RemoteController:
+    """Unitree remote controller data parser for joystick and button state."""
+
+    # ADC parameters for exoskeleton joystick (12-bit ADC)
+    ADC_MAX = 4095
+    ADC_HALF = ADC_MAX / 2
+    JOYSTICK_X_IDX = 11  # X axis in raw ADC array
+    JOYSTICK_BTN_IDX = 12  # Button in raw ADC array
+    JOYSTICK_Y_IDX = 13  # Y axis in raw ADC array
+
+    # Map SDK named buttons to positional indices matching the wireless_remote
+    # byte layout (little-endian uint16 from bytes 2-3).
+    _BUTTON_MAP: list[str] = [
+        "RB",
+        "LB",
+        "start",
+        "back",
+        "RT",
+        "LT",
+        "",
+        "",
+        "A",
+        "B",
+        "X",
+        "Y",
+        "up",
+        "right",
+        "down",
+        "left",
+    ]
+
+    def __init__(self):
+        self.lx = 0.0
+        self.ly = 0.0
+        self.rx = 0.0
+        self.ry = 0.0
+        self.button = [0] * 16
+        self.remote_action = dict.fromkeys(REMOTE_AXES, 0.0)
+
+        # SDK joystick parser for wireless remote bytes
+        self._joystick = Joystick()
+        # Disable axis smoothing and deadzone to preserve raw values
+        for axis in (self._joystick.lx, self._joystick.ly, self._joystick.rx, self._joystick.ry):
+            axis.smooth = 1.0
+            axis.deadzone = 0.0
+
+        # Joystick center calibration (read at connect time)
+        self.left_center_x = self.ADC_HALF
+        self.left_center_y = self.ADC_HALF
+        self.right_center_x = self.ADC_HALF
+        self.right_center_y = self.ADC_HALF
+
+        # Whether to use exo joystick (detected at connect time)
+        self.use_left_exo_joystick = False
+        self.use_right_exo_joystick = False
+
+    def _sync_remote_action(self) -> None:
+        self.remote_action.update(zip(REMOTE_AXES, (self.lx, self.ly, self.rx, self.ry), strict=True))
+
+    def calibrate_center(self, raw16: list[int] | None, side: str) -> None:
+        if raw16 is None or len(raw16) < 16:
+            logger.info(f"{side.capitalize()} exo joystick: no data available")
+            return
+
+        btn_val = raw16[self.JOYSTICK_BTN_IDX]
+        logger.info(f"{side.capitalize()} exo joystick button ADC: {btn_val} (threshold: {self.ADC_HALF})")
+        if btn_val <= self.ADC_HALF:
+            logger.info(f"{side.capitalize()} exo joystick not detected (button below threshold)")
+            return
+
+        x = raw16[self.JOYSTICK_X_IDX]
+        y = raw16[self.JOYSTICK_Y_IDX]
+        if side == "left":
+            self.use_left_exo_joystick = True
+            self.left_center_x, self.left_center_y = x, y
+        else:
+            self.use_right_exo_joystick = True
+            self.right_center_x, self.right_center_y = x, y
+        logger.info(f"{side.capitalize()} exo joystick enabled, center: x={x}, y={y}")
+
+    def set_from_exo(self, raw16: list[int] | None, side: str) -> None:
+        if raw16 is None or len(raw16) < 16:
+            return
+
+        if side == "left":
+            if not self.use_left_exo_joystick:
+                return
+            self.lx = (raw16[self.JOYSTICK_X_IDX] - self.left_center_x) / self.ADC_HALF
+            self.ly = (raw16[self.JOYSTICK_Y_IDX] - self.left_center_y) / self.ADC_HALF
+            self.button[4] = 1 if raw16[self.JOYSTICK_BTN_IDX] < self.ADC_HALF else 0
+            return
+
+        if not self.use_right_exo_joystick:
+            return
+        self.rx = (raw16[self.JOYSTICK_X_IDX] - self.right_center_x) / self.ADC_HALF
+        self.ry = (raw16[self.JOYSTICK_Y_IDX] - self.right_center_y) / self.ADC_HALF
+        self.button[0] = 1 if raw16[self.JOYSTICK_BTN_IDX] < self.ADC_HALF else 0
+
+    def set_from_wireless(self, wireless_remote: bytes) -> None:
+        """Parse Unitree wireless remote raw bytes into joystick + button state."""
+        if len(wireless_remote) < 24:
+            return
+        self._joystick.extract(wireless_remote)
+
+        self.lx = self._joystick.lx.data
+        self.ly = self._joystick.ly.data
+        self.rx = self._joystick.rx.data
+        self.ry = self._joystick.ry.data
+
+        for i, name in enumerate(self._BUTTON_MAP):
+            if name:
+                self.button[i] = getattr(self._joystick, name).data
+
+
 class UnitreeG1Teleoperator(Teleoperator):
    """
    Bimanual exoskeleton arms teleoperator for Unitree G1 arms.
@@ -43,6 +170,13 @@ class UnitreeG1Teleoperator(Teleoperator):
    def __init__(self, config: UnitreeG1TeleoperatorConfig):
        super().__init__(config)
        self.config = config
+        left_exo_enabled = bool(config.left_arm_config.port.strip())
+        right_exo_enabled = bool(config.right_arm_config.port.strip())
+        if left_exo_enabled != right_exo_enabled:
+            raise ValueError(
+                "Invalid exo config: set both left/right exo ports, or leave both empty for remote-only mode."
+            )
+        self._arm_control_enabled = left_exo_enabled and right_exo_enabled

        # Setup calibration directory
        self.calibration_dir = (
@@ -70,24 +204,37 @@ class UnitreeG1Teleoperator(Teleoperator):
        )

        self.ik_helper: ExoskeletonIKHelper | None = None
+        self.remote_controller = RemoteController()

    @cached_property
    def action_features(self) -> dict[str, type]:
-        return {f"{name}.q": float for name in self._g1_joint_names}
+        remote_features = dict.fromkeys(self.remote_controller.remote_action, float)
+        if not self._arm_control_enabled:
+            return remote_features
+        joint_features = {f"{name}.q": float for name in self._g1_arm_joint_names}
+        return {**joint_features, **remote_features}

    @cached_property
    def feedback_features(self) -> dict[str, type]:
-        return {}
+        return {"wireless_remote": bytes}

    @property
    def is_connected(self) -> bool:
+        if not self._arm_control_enabled:
+            return True
        return self.left_arm.is_connected and self.right_arm.is_connected

    @property
    def is_calibrated(self) -> bool:
+        if not self._arm_control_enabled:
+            return True
        return self.left_arm.is_calibrated and self.right_arm.is_calibrated

    def connect(self, calibrate: bool = True) -> None:
+        if not self._arm_control_enabled:
+            logger.warning("Exo ports not fully configured; teleop will send joystick only (no arm actions)")
+            return
+
        self.left_arm.connect(calibrate)
        self.right_arm.connect(calibrate)

@@ -95,6 +242,13 @@ class UnitreeG1Teleoperator(Teleoperator):
        self.ik_helper = ExoskeletonIKHelper(frozen_joints=frozen_joints)
        logger.info("IK helper initialized")

+        time.sleep(0.1)  # Give serial time to populate buffer
+
+        left_raw = self.left_arm.read_raw()
+        right_raw = self.right_arm.read_raw()
+        self.remote_controller.calibrate_center(left_raw, "left")
+        self.remote_controller.calibrate_center(right_raw, "right")
+
    def calibrate(self) -> None:
        if not self.left_arm.is_calibrated:
            logger.info("Starting calibration for left arm...")
@@ -115,12 +269,33 @@ class UnitreeG1Teleoperator(Teleoperator):
        pass

    def get_action(self) -> dict[str, float]:
-        left_angles = self.left_arm.get_angles()
-        right_angles = self.right_arm.get_angles()
-        return self.ik_helper.compute_g1_joints_from_exo(left_angles, right_angles)
+        joint_action = {}
+        left_raw = None
+        right_raw = None
+        if self._arm_control_enabled:
+            left_raw = self.left_arm.read_raw()
+            right_raw = self.right_arm.read_raw()

-    def send_feedback(self, feedback: dict[str, float]) -> None:
-        raise NotImplementedError("Exoskeleton arms do not support feedback")
+            left_angles = self.left_arm.get_angles()
+            right_angles = self.right_arm.get_angles()
+            joint_action = self.ik_helper.compute_g1_joints_from_exo(left_angles, right_angles)
+
+        # Wireless remote has priority when non-zero; otherwise, use exo joystick.
+        rc = self.remote_controller
+        wireless_active = (
+            abs(rc.lx) > 1e-3 or abs(rc.ly) > 1e-3 or abs(rc.rx) > 1e-3 or abs(rc.ry) > 1e-3
+        ) or any(rc.button)
+        if self._arm_control_enabled and not wireless_active:
+            rc.set_from_exo(left_raw, "left")
+            rc.set_from_exo(right_raw, "right")
+
+        rc._sync_remote_action()
+        return {**joint_action, **rc.remote_action}
+
+    def send_feedback(self, feedback: dict[str, Any]) -> None:
+        wireless_remote = feedback.get("wireless_remote")
+        if wireless_remote is not None:
+            self.remote_controller.set_from_wireless(wireless_remote)

    def disconnect(self) -> None:
        self.left_arm.disconnect()
@@ -153,5 +328,5 @@ class UnitreeG1Teleoperator(Teleoperator):
            print("\n\nVisualization stopped.")

    @cached_property
-    def _g1_joint_names(self) -> list[str]:
-        return [joint.name for joint in G1_29_JointIndex]
+    def _g1_arm_joint_names(self) -> list[str]:
+        return [joint.name for joint in G1_29_JointArmIndex]
@@ -74,6 +74,8 @@ _peft_available = is_package_available("peft")
 _scipy_available = is_package_available("scipy")
 _reachy2_sdk_available = is_package_available("reachy2_sdk")
 _can_available = is_package_available("python-can", "can")
+_unitree_sdk_available = is_package_available("unitree-sdk2", "unitree_sdk2py")
+_pygame_available = is_package_available("pygame")


 def make_device_from_device_class(config: ChoiceRegistry) -> Any:
@@ -231,3 +231,39 @@ def test_ready_to_send_observation_with_varying_threshold(robot_client, g_thresh
        robot_client.action_queue.put(act)

    assert robot_client._ready_to_send_observation() is expected
+
+
+# -----------------------------------------------------------------------------
+# Regression test: robot type registry populated by robot_client imports
+# -----------------------------------------------------------------------------
+
+
+def test_robot_client_registers_builtin_robot_types():
+    """Importing robot_client must populate RobotConfig's ChoiceRegistry.
+
+    This is a regression test for a bug introduced in #2425, where removing
+    robot module imports from robot_client.py caused RobotConfig's registry to
+    be empty, breaking CLI argument parsing with:
+      error: argument --robot.type: invalid choice: 'so101_follower' (choose from )
+
+    Robot types are registered via @RobotConfig.register_subclass() decorators
+    at import time, so all supported modules must be explicitly imported.
+    """
+    import lerobot.async_inference.robot_client  # noqa: F401
+    from lerobot.robots.config import RobotConfig
+
+    known_choices = RobotConfig.get_known_choices()
+
+    expected_robot_types = [
+        "so100_follower",
+        "so101_follower",
+        "koch_follower",
+        "omx_follower",
+        "bi_so_follower",
+    ]
+    for robot_type in expected_robot_types:
+        assert robot_type in known_choices, (
+            f"Robot type '{robot_type}' is not registered in RobotConfig's ChoiceRegistry. "
+            f"Ensure the corresponding module is imported in robot_client.py. "
+            f"Known choices: {sorted(known_choices)}"
+        )
@@ -170,6 +170,7 @@ def test_async_read(index_or_path):
        assert isinstance(img, np.ndarray)


+@pytest.mark.skip("Skipping test: async_read  0 timeout behavior may be flaky/non-deterministic.")
 def test_async_read_timeout():
    config = OpenCVCameraConfig(index_or_path=DEFAULT_PNG_FILE_PATH, warmup_s=0)

@@ -40,7 +40,7 @@ from lerobot.utils.constants import (
    OBS_LANGUAGE_TOKENS,
    OBS_STATE,
 )  # noqa: E402
-from tests.utils import require_cuda  # noqa: E402
+from tests.utils import require_cuda, require_hf_token  # noqa: E402

 # Constants
 DUMMY_ACTION_DIM = 7
@@ -65,6 +65,7 @@ EXPECTED_ACTIONS_FIRST_5 = torch.tensor([0.0000, 0.3536, 0.0707, 0.0000, 0.0000]


@require_cuda
+@require_hf_token
 def set_seed_all(seed: int):
    """Set random seed for all RNG sources to ensure reproducibility."""
    random.seed(seed)
@@ -82,6 +83,7 @@ def set_seed_all(seed: int):


@require_cuda
+@require_hf_token
 def instantiate_lerobot_pi0_fast(
    from_pretrained: bool = False,
    model_path: str = MODEL_PATH_LEROBOT,
@@ -125,6 +127,7 @@ def instantiate_lerobot_pi0_fast(


@require_cuda
+@require_hf_token
 def create_dummy_data(device=DEVICE):
    """Create dummy data for testing both implementations."""
    batch_size = 1
@@ -157,6 +160,7 @@ def create_dummy_data(device=DEVICE):
 # Pytest fixtures
@pytest.fixture(scope="module")
@require_cuda
+@require_hf_token
 def pi0_fast_components():
    """Fixture to instantiate and provide all PI0Fast components for tests."""
    print(f"\nTesting with DEVICE='{DEVICE}'")
@@ -168,6 +172,7 @@ def pi0_fast_components():

@pytest.fixture(scope="module")
@require_cuda
+@require_hf_token
 def policy(pi0_fast_components):
    """Fixture to provide the PI0Fast policy for tests."""
    return pi0_fast_components[0]
@@ -175,12 +180,14 @@ def policy(pi0_fast_components):

@pytest.fixture(scope="module")
@require_cuda
+@require_hf_token
 def preprocessor(pi0_fast_components):
    """Fixture to provide the PI0Fast preprocessor for tests."""
    return pi0_fast_components[1]


@require_cuda
+@require_hf_token
 def test_pi0_fast_preprocessor_alignment(policy, preprocessor):
    """Test that LeRobot PI0Fast preprocessor produces expected outputs."""
    print("\n" + "=" * 80)
@@ -228,6 +235,7 @@ def test_pi0_fast_preprocessor_alignment(policy, preprocessor):


@require_cuda
+@require_hf_token
 def test_pi0_fast_action_generation(policy, preprocessor):
    """Test PI0Fast LeRobot implementation generates expected actions."""
    print("\n" + "=" * 80)
@@ -306,6 +314,7 @@ def test_pi0_fast_action_generation(policy, preprocessor):


@require_cuda
+@require_hf_token
 def test_pi0_fast_inference_reproducibility(policy, preprocessor):
    """Test that PI0Fast inference is reproducible with the same seed."""
    print("\n" + "=" * 80)
@@ -347,6 +356,7 @@ def test_pi0_fast_inference_reproducibility(policy, preprocessor):


@require_cuda
+@require_hf_token
 def test_pi0_fast_forward_pass_logits(policy, preprocessor):
    """Test PI0Fast forward pass and compare logits against expected values."""
    print("\n" + "=" * 80)
@@ -396,6 +406,7 @@ def test_pi0_fast_forward_pass_logits(policy, preprocessor):


@require_cuda
+@require_hf_token
 def test_pi0_fast_action_token_sampling(policy, preprocessor):
    """Test PI0Fast action token sampling (autoregressive decoding)."""
    print("\n" + "=" * 80)
@@ -452,6 +463,7 @@ def test_pi0_fast_action_token_sampling(policy, preprocessor):


@require_cuda
+@require_hf_token
 def test_pi0_fast_detokenization(policy, preprocessor):
    """Test PI0Fast action detokenization (FAST decoding)."""
    print("\n" + "=" * 80)
@@ -14,10 +14,13 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.

-"""Test script to verify PI0 policy integration with LeRobot, only meant to be run locally!"""
+"""Test script to verify PI0 policy integration with LeRobot"""

+import pytest
 import torch

+pytest.importorskip("transformers")
+
 from lerobot.policies.factory import make_policy_config  # noqa: E402
 from lerobot.policies.pi0 import (  # noqa: E402
    PI0Config,
@@ -25,10 +28,11 @@ from lerobot.policies.pi0 import (  # noqa: E402
    make_pi0_pre_post_processors,  # noqa: E402
 )
 from lerobot.utils.random_utils import set_seed  # noqa: E402
-from tests.utils import require_cuda  # noqa: E402
+from tests.utils import require_cuda, require_hf_token  # noqa: E402


@require_cuda
+@require_hf_token
 def test_policy_instantiation():
    # Create config
    set_seed(42)
@@ -105,6 +109,7 @@ def test_policy_instantiation():


@require_cuda
+@require_hf_token
 def test_config_creation():
    """Test policy config creation through factory."""
    try:
@@ -14,10 +14,13 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.

-"""Test script to verify PI0.5 (pi05) support in PI0 policy, only meant to be run locally!"""
+"""Test script to verify PI0.5 (pi05) support in PI0 policy"""

+import pytest
 import torch

+pytest.importorskip("transformers")
+
 from lerobot.policies.factory import make_policy_config  # noqa: E402
 from lerobot.policies.pi05 import (  # noqa: E402
    PI05Config,
@@ -25,10 +28,11 @@ from lerobot.policies.pi05 import (  # noqa: E402
    make_pi05_pre_post_processors,  # noqa: E402
 )
 from lerobot.utils.random_utils import set_seed
-from tests.utils import require_cuda  # noqa: E402
+from tests.utils import require_cuda, require_hf_token  # noqa: E402


@require_cuda
+@require_hf_token
 def test_policy_instantiation():
    # Create config
    set_seed(42)
@@ -141,6 +145,7 @@ def test_policy_instantiation():


@require_cuda
+@require_hf_token
 def test_config_creation():
    """Test policy config creation through factory."""
    try:
@@ -14,7 +14,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.

-"""Test script to verify PI0OpenPI policy integration with LeRobot vs the original implementation, only meant to be run locally!"""
+"""Test script to verify PI0OpenPI policy integration with LeRobot vs the original implementation"""

 import os
 from copy import deepcopy
@@ -14,7 +14,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.

-"""Test script to verify PI0 policy integration with LeRobot vs the original implementation, only meant to be run locally!"""
+"""Test script to verify PI0 policy integration with LeRobot vs the original implementation"""

 import os
 from copy import deepcopy
@@ -14,7 +14,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.

-"""Test script to verify Wall-X policy integration with LeRobot, only meant to be run locally!"""
+"""Test script to verify Wall-X policy integration with LeRobot"""

 import pytest
 import torch
@@ -29,10 +29,11 @@ from lerobot.policies.wall_x import WallXConfig  # noqa: E402
 from lerobot.policies.wall_x.modeling_wall_x import WallXPolicy  # noqa: E402
 from lerobot.policies.wall_x.processor_wall_x import make_wall_x_pre_post_processors  # noqa: E402
 from lerobot.utils.random_utils import set_seed  # noqa: E402
-from tests.utils import require_cuda  # noqa: E402
+from tests.utils import require_cuda, require_hf_token  # noqa: E402


@require_cuda
+@require_hf_token
 def test_policy_instantiation():
    # Create config
    set_seed(42)
@@ -118,6 +119,7 @@ def test_policy_instantiation():


@require_cuda
+@require_hf_token
 def test_config_creation():
    """Test policy config creation through factory."""
    try:
@@ -14,7 +14,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.

-"""Test script to verify XVLA policy integration with LeRobot vs the original implementation, only meant to be run locally!"""
+"""Test script to verify XVLA policy integration with LeRobot vs the original implementation"""
 # ruff: noqa: E402

 import random
@@ -0,0 +1,267 @@
+#!/usr/bin/env python
+
+# Copyright 2026 The HuggingFace Inc. team. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+"""Tests for Unitree G1 robot. Meant to be run in an environment where the Unitree SDK is installed."""
+
+from unittest.mock import MagicMock, patch
+
+import numpy as np
+import pytest
+
+from lerobot.utils.import_utils import _unitree_sdk_available
+
+if not _unitree_sdk_available:
+    pytest.skip("Unitree SDK not available", allow_module_level=True)
+
+from lerobot.robots.unitree_g1.config_unitree_g1 import UnitreeG1Config
+from lerobot.robots.unitree_g1.g1_utils import (
+    NUM_MOTORS,
+    REMOTE_AXES,
+    REMOTE_BUTTONS,
+    REMOTE_KEYS,
+    G1_29_JointArmIndex,
+    G1_29_JointIndex,
+    default_remote_input,
+    get_gravity_orientation,
+)
+
+# ---------------------------------------------------------------------------
+# Unit tests for g1_utils (no SDK needed)
+# ---------------------------------------------------------------------------
+
+
+class TestG1Utils:
+    def test_num_motors(self):
+        assert NUM_MOTORS == 29
+
+    def test_joint_index_count(self):
+        assert len(G1_29_JointIndex) == 29
+
+    def test_joint_arm_index_count(self):
+        assert len(G1_29_JointArmIndex) == 14
+
+    def test_arm_indices_are_subset_of_full(self):
+        full_values = {j.value for j in G1_29_JointIndex}
+        arm_values = {j.value for j in G1_29_JointArmIndex}
+        assert arm_values.issubset(full_values)
+
+    def test_arm_indices_start_at_15(self):
+        assert min(j.value for j in G1_29_JointArmIndex) == 15
+        assert max(j.value for j in G1_29_JointArmIndex) == 28
+
+    def test_enum_naming_consistency(self):
+        """Verify all wrist joints use consistent PascalCase naming."""
+        wrist_joints = [j for j in G1_29_JointIndex if "Wrist" in j.name]
+        for j in wrist_joints:
+            # Should be "WristYaw", "WristPitch", "WristRoll" — no lowercase after "Wrist"
+            after_wrist = j.name.split("Wrist")[1]
+            assert after_wrist[0].isupper(), f"{j.name} has inconsistent casing after 'Wrist'"
+
+    def test_remote_keys_structure(self):
+        assert len(REMOTE_AXES) == 4
+        assert len(REMOTE_BUTTONS) == 16
+        assert len(REMOTE_KEYS) == 20
+        assert REMOTE_KEYS == REMOTE_AXES + REMOTE_BUTTONS
+
+    def test_default_remote_input(self):
+        d = default_remote_input()
+        assert len(d) == 20
+        assert all(v == 0.0 for v in d.values())
+        assert set(d.keys()) == set(REMOTE_KEYS)
+
+    def test_gravity_orientation_identity(self):
+        """Quaternion [1, 0, 0, 0] (no rotation) should give gravity along -z."""
+        g = get_gravity_orientation([1.0, 0.0, 0.0, 0.0])
+        assert g.shape == (3,)
+        assert g.dtype == np.float32
+        np.testing.assert_allclose(g, [0.0, 0.0, -1.0], atol=1e-6)
+
+    def test_gravity_orientation_dtype(self):
+        g = get_gravity_orientation(np.array([1.0, 0.0, 0.0, 0.0]))
+        assert g.dtype == np.float32
+
+
+# ---------------------------------------------------------------------------
+# Unit tests for UnitreeG1Config (no SDK needed)
+# ---------------------------------------------------------------------------
+
+
+class TestUnitreeG1Config:
+    def test_default_config(self):
+        cfg = UnitreeG1Config()
+        assert len(cfg.kp) == 29
+        assert len(cfg.kd) == 29
+        assert len(cfg.default_positions) == 29
+        assert cfg.is_simulation is True
+        assert cfg.controller is None
+        assert cfg.gravity_compensation is False
+
+    def test_gains_are_positive(self):
+        cfg = UnitreeG1Config()
+        assert all(v > 0 for v in cfg.kp)
+        assert all(v > 0 for v in cfg.kd)
+
+    def test_config_copies_gains(self):
+        """Each config instance should have its own copy of gains."""
+        cfg1 = UnitreeG1Config()
+        cfg2 = UnitreeG1Config()
+        cfg1.kp[0] = 999.0
+        assert cfg2.kp[0] != 999.0
+
+
+# ---------------------------------------------------------------------------
+# Robot mock and integration tests
+# ---------------------------------------------------------------------------
+
+
+def _make_lowstate_msg_mock():
+    """Create a mock that mimics the SDK LowState_ message."""
+    msg = MagicMock()
+    for i in range(29):
+        motor = MagicMock()
+        motor.q = float(i) * 0.1
+        motor.dq = float(i) * 0.01
+        motor.tau_est = float(i) * 0.001
+        motor.temperature = 30.0 + i
+        msg.motor_state.__getitem__ = lambda self, idx, _motors={}: _motors.setdefault(
+            idx, MagicMock(q=idx * 0.1, dq=idx * 0.01, tau_est=idx * 0.001, temperature=30.0 + idx)
+        )
+
+    msg.imu_state.quaternion = [1.0, 0.0, 0.0, 0.0]
+    msg.imu_state.gyroscope = [0.1, 0.2, 0.3]
+    msg.imu_state.accelerometer = [0.0, 0.0, 9.81]
+    msg.imu_state.rpy = [0.0, 0.0, 0.0]
+    msg.imu_state.temperature = 25.0
+    msg.wireless_remote = b"\x00" * 40
+    msg.mode_machine = 0
+    return msg
+
+
+def _make_sdk_mocks():
+    """Create mocks for the Unitree SDK modules used by UnitreeG1."""
+    lowcmd_default = MagicMock()
+    lowcmd_default.mode_pr = 0
+    lowcmd_default.motor_cmd = [MagicMock() for _ in range(35)]
+
+    crc_mock = MagicMock()
+    crc_mock.Crc.return_value = 0
+
+    lowstate_msg = _make_lowstate_msg_mock()
+
+    subscriber_mock = MagicMock()
+    subscriber_mock.Read.return_value = lowstate_msg
+
+    publisher_mock = MagicMock()
+
+    return {
+        "lowcmd_default": lowcmd_default,
+        "crc_mock": crc_mock,
+        "subscriber_mock": subscriber_mock,
+        "publisher_mock": publisher_mock,
+        "lowstate_msg": lowstate_msg,
+    }
+
+
+@pytest.fixture
+def unitree_g1():
+    """Create a UnitreeG1 robot with all SDK dependencies mocked."""
+    mocks = _make_sdk_mocks()
+
+    mock_channel_init = MagicMock()
+    mock_channel_pub = MagicMock(return_value=mocks["publisher_mock"])
+    mock_channel_sub = MagicMock(return_value=mocks["subscriber_mock"])
+
+    with (
+        patch(
+            "lerobot.robots.unitree_g1.unitree_g1.make_cameras_from_configs",
+            return_value={},
+        ),
+        patch(
+            "lerobot.robots.unitree_g1.unitree_g1.G1_29_ArmIK",
+            return_value=MagicMock(),
+        ),
+        patch(
+            "lerobot.robots.unitree_g1.unitree_g1._SDKChannelFactoryInitialize",
+            mock_channel_init,
+        ),
+        patch(
+            "lerobot.robots.unitree_g1.unitree_g1._SDKChannelPublisher",
+            mock_channel_pub,
+        ),
+        patch(
+            "lerobot.robots.unitree_g1.unitree_g1._SDKChannelSubscriber",
+            mock_channel_sub,
+        ),
+        patch(
+            "lerobot.robots.unitree_g1.unitree_g1.unitree_hg_msg_dds__LowCmd_",
+            MagicMock(return_value=mocks["lowcmd_default"]),
+        ),
+        patch(
+            "lerobot.robots.unitree_g1.unitree_g1.hg_LowCmd",
+            MagicMock,
+        ),
+        patch(
+            "lerobot.robots.unitree_g1.unitree_g1.hg_LowState",
+            MagicMock,
+        ),
+        patch(
+            "lerobot.robots.unitree_g1.unitree_g1.CRC",
+            MagicMock(return_value=mocks["crc_mock"]),
+        ),
+    ):
+        from lerobot.robots.unitree_g1.unitree_g1 import UnitreeG1
+
+        cfg = UnitreeG1Config(is_simulation=True, gravity_compensation=False)
+        robot = UnitreeG1(cfg)
+        yield robot, mocks
+        if robot.is_connected:
+            robot.disconnect()
+
+
+def test_init_state(unitree_g1):
+    robot, _ = unitree_g1
+    assert not robot.is_connected
+    assert robot.controller is None
+
+
+def test_observation_features(unitree_g1):
+    robot, _ = unitree_g1
+    features = robot.observation_features
+    # Should have .q for all 29 joints (no cameras configured)
+    assert len(features) == 29
+    for joint in G1_29_JointIndex:
+        assert f"{joint.name}.q" in features
+
+
+def test_action_features_no_controller(unitree_g1):
+    robot, _ = unitree_g1
+    features = robot.action_features
+    # Without controller: all 29 joints
+    assert len(features) == 29
+    for joint in G1_29_JointIndex:
+        assert f"{joint.name}.q" in features
+
+
+def test_get_observation_before_connect(unitree_g1):
+    robot, _ = unitree_g1
+    obs = robot.get_observation()
+    assert obs == {}
+
+
+def test_disconnect_idempotent(unitree_g1):
+    robot, _ = unitree_g1
+    # Should not raise even when not connected
+    robot.disconnect()
@@ -0,0 +1,309 @@
+#!/usr/bin/env python
+
+# Copyright 2026 The HuggingFace Inc. team. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+"""Tests for Unitree G1 teleoperator. Meant to be run in an environment where the Unitree SDK is installed."""
+
+from unittest.mock import MagicMock
+
+import pytest
+
+from lerobot.utils.import_utils import _unitree_sdk_available
+
+if not _unitree_sdk_available:
+    pytest.skip("Unitree SDK not available", allow_module_level=True)
+
+from lerobot.robots.unitree_g1.g1_utils import REMOTE_AXES
+from lerobot.teleoperators.unitree_g1.config_unitree_g1 import (
+    ExoskeletonArmPortConfig,
+    UnitreeG1TeleoperatorConfig,
+)
+from lerobot.teleoperators.unitree_g1.unitree_g1 import RemoteController, UnitreeG1Teleoperator
+
+# ---------------------------------------------------------------------------
+# Tests for RemoteController
+# ---------------------------------------------------------------------------
+
+
+def _make_joystick_mock():
+    """Create a mock Joystick class matching the SDK interface."""
+    joystick = MagicMock()
+    # Axes are Axis objects with .data attribute
+    joystick.lx = MagicMock(data=0.0, smooth=0.03, deadzone=0.01)
+    joystick.ly = MagicMock(data=0.0, smooth=0.03, deadzone=0.01)
+    joystick.rx = MagicMock(data=0.0, smooth=0.03, deadzone=0.01)
+    joystick.ry = MagicMock(data=0.0, smooth=0.03, deadzone=0.01)
+    # Buttons are Button objects with .data attribute
+    for name in ["RB", "LB", "start", "back", "RT", "LT", "A", "B", "X", "Y", "up", "right", "down", "left"]:
+        setattr(joystick, name, MagicMock(data=0))
+    return joystick
+
+
+@pytest.fixture
+def remote_controller():
+    """Create a RemoteController with a mocked Joystick."""
+    mock_joystick = _make_joystick_mock()
+
+    rc = RemoteController()
+    rc._joystick = mock_joystick
+    yield rc, mock_joystick
+
+
+def test_remote_controller_init(remote_controller):
+    rc, _ = remote_controller
+    assert rc.lx == 0.0
+    assert rc.ly == 0.0
+    assert rc.rx == 0.0
+    assert rc.ry == 0.0
+    assert len(rc.button) == 16
+    assert all(b == 0 for b in rc.button)
+
+
+def test_sync_remote_action(remote_controller):
+    rc, _ = remote_controller
+    rc.lx = 0.5
+    rc.ly = -0.3
+    rc.rx = 0.1
+    rc.ry = 0.0
+    rc._sync_remote_action()
+
+    assert rc.remote_action["remote.lx"] == 0.5
+    assert rc.remote_action["remote.ly"] == -0.3
+    assert rc.remote_action["remote.rx"] == 0.1
+    assert rc.remote_action["remote.ry"] == 0.0
+
+
+def test_set_from_wireless_calls_extract(remote_controller):
+    rc, mock_joystick = remote_controller
+    # Set up the mock to populate data after extract
+    mock_joystick.lx.data = 0.5
+    mock_joystick.ly.data = -0.3
+    mock_joystick.rx.data = 0.1
+    mock_joystick.ry.data = 0.0
+
+    wireless_data = b"\x00" * 40
+    rc.set_from_wireless(wireless_data)
+
+    mock_joystick.extract.assert_called_once_with(wireless_data)
+    assert rc.lx == 0.5
+    assert rc.ly == -0.3
+
+
+def test_set_from_wireless_short_data(remote_controller):
+    rc, mock_joystick = remote_controller
+    rc.set_from_wireless(b"\x00" * 10)  # Too short
+    mock_joystick.extract.assert_not_called()
+
+
+def test_set_from_wireless_buttons(remote_controller):
+    rc, mock_joystick = remote_controller
+    # Simulate RB pressed
+    mock_joystick.RB.data = 1
+    mock_joystick.lx.data = 0.0
+    mock_joystick.ly.data = 0.0
+    mock_joystick.rx.data = 0.0
+    mock_joystick.ry.data = 0.0
+
+    rc.set_from_wireless(b"\x00" * 40)
+    assert rc.button[0] == 1  # RB maps to button[0]
+
+
+def test_set_from_exo_left(remote_controller):
+    rc, _ = remote_controller
+    rc.use_left_exo_joystick = True
+    rc.left_center_x = 2048
+    rc.left_center_y = 2048
+
+    raw16 = [0] * 16
+    raw16[11] = 3048  # X axis: (3048 - 2048) / 2047.5 ≈ 0.488
+    raw16[13] = 1048  # Y axis: (1048 - 2048) / 2047.5 ≈ -0.488
+    raw16[12] = 0  # Button pressed (below ADC_HALF)
+
+    rc.set_from_exo(raw16, "left")
+    assert rc.lx == pytest.approx((3048 - 2048) / 2047.5, abs=1e-3)
+    assert rc.ly == pytest.approx((1048 - 2048) / 2047.5, abs=1e-3)
+    assert rc.button[4] == 1  # Left button maps to button[4]
+
+
+def test_set_from_exo_clears_button(remote_controller):
+    rc, _ = remote_controller
+    rc.use_left_exo_joystick = True
+    rc.button[4] = 1  # Pre-set
+
+    raw16 = [0] * 16
+    raw16[12] = 4000  # Button NOT pressed (above ADC_HALF)
+
+    rc.set_from_exo(raw16, "left")
+    assert rc.button[4] == 0  # Should be cleared
+
+
+def test_set_from_exo_ignored_when_not_enabled(remote_controller):
+    rc, _ = remote_controller
+    rc.use_left_exo_joystick = False
+    raw16 = [0] * 16
+    raw16[11] = 3000
+
+    rc.set_from_exo(raw16, "left")
+    assert rc.lx == 0.0  # Unchanged
+
+
+# ---------------------------------------------------------------------------
+# Tests for UnitreeG1TeleoperatorConfig (no SDK needed)
+# ---------------------------------------------------------------------------
+
+
+class TestTeleoperatorConfig:
+    def test_default_config(self):
+        cfg = UnitreeG1TeleoperatorConfig()
+        assert cfg.left_arm_config.port == ""
+        assert cfg.right_arm_config.port == ""
+        assert cfg.frozen_joints == ""
+
+    def test_config_with_ports(self):
+        cfg = UnitreeG1TeleoperatorConfig(
+            left_arm_config=ExoskeletonArmPortConfig(port="/dev/ttyACM0"),
+            right_arm_config=ExoskeletonArmPortConfig(port="/dev/ttyACM1"),
+        )
+        assert cfg.left_arm_config.port == "/dev/ttyACM0"
+        assert cfg.right_arm_config.port == "/dev/ttyACM1"
+
+
+# ---------------------------------------------------------------------------
+# Tests for UnitreeG1Teleoperator
+# ---------------------------------------------------------------------------
+
+
+@pytest.fixture
+def teleop_remote_only():
+    """Create a UnitreeG1Teleoperator in remote-only mode (no exo arms)."""
+    cfg = UnitreeG1TeleoperatorConfig()  # No ports = remote-only mode
+    teleop = UnitreeG1Teleoperator(cfg)
+    yield teleop
+
+
+def test_remote_only_connect(teleop_remote_only):
+    """Remote-only mode should connect immediately without serial ports."""
+    teleop = teleop_remote_only
+    teleop.connect()
+    assert teleop.is_connected
+    assert not teleop._arm_control_enabled
+
+
+def test_remote_only_action_features(teleop_remote_only):
+    teleop = teleop_remote_only
+    features = teleop.action_features
+    # Remote-only: just the 4 remote axes
+    assert set(features.keys()) == set(REMOTE_AXES)
+
+
+def test_feedback_features(teleop_remote_only):
+    teleop = teleop_remote_only
+    features = teleop.feedback_features
+    assert "wireless_remote" in features
+    assert features["wireless_remote"] is bytes
+
+
+def test_remote_only_get_action(teleop_remote_only):
+    teleop = teleop_remote_only
+    teleop.connect()
+    action = teleop.get_action()
+    assert set(action.keys()) == set(REMOTE_AXES)
+    assert all(isinstance(v, float) for v in action.values())
+
+
+def test_send_feedback(teleop_remote_only):
+    teleop = teleop_remote_only
+    teleop.connect()
+    # Should not raise
+    teleop.send_feedback({"wireless_remote": b"\x00" * 40})
+
+
+def test_send_feedback_missing_key(teleop_remote_only):
+    teleop = teleop_remote_only
+    teleop.connect()
+    # Should not raise even with missing key
+    teleop.send_feedback({"other_key": 42})
+
+
+def test_asymmetric_exo_ports_raises():
+    """Configuring only one exo port should raise ValueError."""
+    cfg = UnitreeG1TeleoperatorConfig(
+        left_arm_config=ExoskeletonArmPortConfig(port="/dev/ttyACM0"),
+        # right_arm_config left empty
+    )
+    with pytest.raises(ValueError, match="set both left/right"):
+        UnitreeG1Teleoperator(cfg)
+
+
+# ---------------------------------------------------------------------------
+# Tests for ExoskeletonArm (needs serial mock)
+# ---------------------------------------------------------------------------
+
+
+class TestExoskeletonArm:
+    def test_parse_raw16_valid(self):
+        from lerobot.teleoperators.unitree_g1.exo_serial import parse_raw16
+
+        line = b"100 200 300 400 500 600 700 800 900 1000 1100 1200 1300 1400 1500 1600\n"
+        result = parse_raw16(line)
+        assert result is not None
+        assert len(result) == 16
+        assert result[0] == 100
+        assert result[15] == 1600
+
+    def test_parse_raw16_too_short(self):
+        from lerobot.teleoperators.unitree_g1.exo_serial import parse_raw16
+
+        line = b"100 200 300\n"
+        assert parse_raw16(line) is None
+
+    def test_parse_raw16_garbage(self):
+        from lerobot.teleoperators.unitree_g1.exo_serial import parse_raw16
+
+        assert parse_raw16(b"not numbers at all\n") is None
+        assert parse_raw16(b"\xff\xfe\xfd\n") is None
+        assert parse_raw16(b"") is None
+
+    def test_calibrate_requires_connection(self):
+        from lerobot.teleoperators.unitree_g1.exo_serial import ExoskeletonArm
+
+        arm = ExoskeletonArm(
+            port="/dev/null",
+            calibration_fpath=MagicMock(is_file=MagicMock(return_value=False)),
+            side="left",
+        )
+        with pytest.raises(RuntimeError, match="not connected"):
+            arm.calibrate()
+
+    def test_is_connected_false_by_default(self):
+        from lerobot.teleoperators.unitree_g1.exo_serial import ExoskeletonArm
+
+        arm = ExoskeletonArm(
+            port="/dev/null",
+            calibration_fpath=MagicMock(is_file=MagicMock(return_value=False)),
+            side="left",
+        )
+        assert not arm.is_connected
+        assert not arm.is_calibrated
+
+    def test_read_raw_when_disconnected(self):
+        from lerobot.teleoperators.unitree_g1.exo_serial import ExoskeletonArm
+
+        arm = ExoskeletonArm(
+            port="/dev/null",
+            calibration_fpath=MagicMock(is_file=MagicMock(return_value=False)),
+            side="left",
+        )
+        assert arm.read_raw() is None
@@ -0,0 +1,176 @@
+#!/usr/bin/env python
+
+# Copyright 2025 The HuggingFace Inc. team. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+"""Tests for RoboCasa LeRobot integration.
+
+Requires: robocasa installed + kitchen assets downloaded.
+Tests are skipped automatically if robocasa is not available.
+"""
+from __future__ import annotations
+
+import numpy as np
+import pytest
+
+# Skip entire module if robocasa is not installed or assets are missing
+robocasa = pytest.importorskip("robocasa", reason="robocasa not installed")
+
+from lerobot.envs.robocasa import ACTION_DIM, STATE_DIM, CAM_KEY_TO_NAME, RoboCasaEnv, create_robocasa_envs
+
+# The 5 benchmark tasks (3 short + 2 long)
+BENCHMARK_TASKS = [
+    "PickPlaceCounterToCabinet",  # short
+    "PrepareToast",               # short
+    "CoffeeSetupMug",             # short
+    "PrepareCoffee",              # long
+    "RestockPantry",              # long
+]
+SHORT_TASKS = BENCHMARK_TASKS[:3]
+LONG_TASKS = BENCHMARK_TASKS[3:]
+
+IMAGE_SIZE = 64  # small for fast tests
+
+
+@pytest.fixture(scope="module")
+def single_env():
+    """Shared env instance for lightweight tests."""
+    env = RoboCasaEnv(task="PickPlaceCounterToCabinet", image_size=IMAGE_SIZE)
+    yield env
+    env.close()
+
+
+class TestRoboCasaEnvSpaces:
+    def test_action_space_is_flat_box(self, single_env):
+        import gymnasium as gym
+
+        assert isinstance(single_env.action_space, gym.spaces.Box)
+        assert single_env.action_space.shape == (ACTION_DIM,)
+        assert single_env.action_space.dtype == np.float32
+
+    def test_action_bounds(self, single_env):
+        assert np.all(single_env.action_space.low == -1.0)
+        assert np.all(single_env.action_space.high == 1.0)
+
+    def test_observation_space_has_pixels_and_state(self, single_env):
+        import gymnasium as gym
+
+        assert isinstance(single_env.observation_space, gym.spaces.Dict)
+        assert "pixels" in single_env.observation_space.spaces
+        assert "robot_state" in single_env.observation_space.spaces
+
+    def test_observation_space_cameras(self, single_env):
+        pixels_space = single_env.observation_space["pixels"]
+        expected_cams = set(CAM_KEY_TO_NAME.values())
+        assert set(pixels_space.spaces.keys()) == expected_cams
+
+    def test_state_dim(self, single_env):
+        state_space = single_env.observation_space["robot_state"]
+        assert state_space.shape == (STATE_DIM,)
+
+
+class TestRoboCasaEnvReset:
+    def test_reset_returns_obs_and_info(self, single_env):
+        obs, info = single_env.reset()
+        assert isinstance(obs, dict)
+        assert isinstance(info, dict)
+
+    def test_reset_obs_has_pixels(self, single_env):
+        obs, _ = single_env.reset()
+        assert "pixels" in obs
+        for cam_name in CAM_KEY_TO_NAME.values():
+            assert cam_name in obs["pixels"], f"Missing camera: {cam_name}"
+
+    def test_reset_obs_image_shape(self, single_env):
+        obs, _ = single_env.reset()
+        for cam_name, img in obs["pixels"].items():
+            assert img.shape == (IMAGE_SIZE, IMAGE_SIZE, 3), f"Bad shape for {cam_name}: {img.shape}"
+            assert img.dtype == np.uint8
+
+    def test_reset_obs_state_shape(self, single_env):
+        obs, _ = single_env.reset()
+        assert obs["robot_state"].shape == (STATE_DIM,)
+        assert obs["robot_state"].dtype == np.float32
+
+    def test_reset_info_has_task(self, single_env):
+        _, info = single_env.reset()
+        assert "task" in info
+        assert info["task"] == "PickPlaceCounterToCabinet"
+
+
+class TestRoboCasaEnvStep:
+    def test_step_10_random_actions(self, single_env):
+        single_env.reset()
+        for _ in range(10):
+            action = single_env.action_space.sample()
+            obs, reward, terminated, truncated, info = single_env.step(action)
+        assert obs["robot_state"].shape == (STATE_DIM,)
+        assert isinstance(reward, float)
+        assert isinstance(terminated, bool)
+        assert isinstance(truncated, bool)
+
+    def test_step_bad_action_raises(self, single_env):
+        single_env.reset()
+        with pytest.raises(ValueError, match="Expected 1-D action"):
+            single_env.step(np.zeros((2, ACTION_DIM)))
+
+    def test_step_info_has_is_success(self, single_env):
+        single_env.reset()
+        _, _, _, _, info = single_env.step(single_env.action_space.sample())
+        assert "is_success" in info
+
+
+class TestRoboCasaConfig:
+    def test_robocasa_env_config(self):
+        from lerobot.envs.configs import RoboCasaEnv as RoboCasaEnvConfig
+        from lerobot.configs.types import FeatureType
+
+        cfg = RoboCasaEnvConfig(task="PickPlaceCounterToCabinet", image_size=IMAGE_SIZE)
+        assert cfg.type == "robocasa"
+        # action feature
+        assert "action" in cfg.features
+        assert cfg.features["action"].shape == (ACTION_DIM,)
+        # camera features
+        for cam in ("agentview_left", "agentview_right", "eye_in_hand"):
+            assert cam in cfg.features
+            assert cfg.features[cam].type == FeatureType.VISUAL
+            assert cfg.features[cam].shape == (IMAGE_SIZE, IMAGE_SIZE, 3)
+        # state feature
+        assert "robot_state" in cfg.features
+        assert cfg.features["robot_state"].shape == (STATE_DIM,)
+
+    def test_make_env_config_robocasa(self):
+        from lerobot.envs.factory import make_env_config
+        cfg = make_env_config("robocasa", task="PickPlaceCounterToCabinet")
+        assert cfg.type == "robocasa"
+
+
+class TestRoboCasaProcessorStep:
+    def test_processor_remaps_keys(self):
+        import torch
+        from lerobot.processor.env_processor import RoboCasaProcessorStep
+        from lerobot.utils.constants import OBS_IMAGES, OBS_STATE
+
+        step = RoboCasaProcessorStep()
+        B = 2
+        obs = {
+            f"{OBS_IMAGES}.agentview_left":  torch.zeros(B, 3, IMAGE_SIZE, IMAGE_SIZE),
+            f"{OBS_IMAGES}.agentview_right": torch.zeros(B, 3, IMAGE_SIZE, IMAGE_SIZE),
+            f"{OBS_IMAGES}.eye_in_hand":     torch.zeros(B, 3, IMAGE_SIZE, IMAGE_SIZE),
+            f"observation.robot_state":      torch.zeros(B, STATE_DIM),
+        }
+        out = step._process_observation(obs)
+        assert OBS_STATE in out
+        assert out[OBS_STATE].dtype == torch.float32
+        for cam in ("agentview_left", "agentview_right", "eye_in_hand"):
+            assert f"{OBS_IMAGES}.{cam}" in out
@@ -108,6 +108,22 @@ def require_cuda(func):
    return wrapper


+def require_hf_token(func):
+    """
+    Decorator that skips the test if no Hugging Face Hub token is available.
+    """
+
+    @wraps(func)
+    def wrapper(*args, **kwargs):
+        from huggingface_hub import get_token
+
+        if get_token() is None:
+            pytest.skip("requires HF token for gated model access")
+        return func(*args, **kwargs)
+
+    return wrapper
+
+
 def require_env(func):
    """
    Decorator that skips the test if the required environment package is not installed.
Author	SHA1	Message	Date
Pepijn	8904768db4	feat(envs): add RoboCasa composite-task benchmark integration Integrates 5 selected RoboCasa kitchen tasks (3 short + 2 long) as a LeRobot benchmark environment, following the same pattern as Libero. Selected tasks: Short: PickPlaceCounterToCabinet, PrepareToast, CoffeeSetupMug Long: PrepareCoffee, RestockPantry Changes: - envs/robocasa.py: RoboCasaEnv wrapper with flat 12D Box action space, 3-camera pixel obs, and 16D proprioceptive state - envs/configs.py: RoboCasaEnv config with features_map - envs/factory.py: wire robocasa into make_env + make_env_pre_post_processors - processor/env_processor.py: RoboCasaProcessorStep for obs key remapping - tests/test_robocasa_env.py: full test suite (auto-skips if assets missing) Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>	2026-03-09 17:08:32 +01:00
Steven Palma	b0efa73520	chore(dependencies): Bump lerobot to 0.5.1 (#3118 )	2026-03-09 12:43:32 +01:00
Steven Palma	00b662de02	chore(dependencies): Bump lerobot to 0.5.0 (#3117 )	2026-03-09 11:34:52 +01:00
Steven Palma	5c51a74484	chore(deps): update requirements file (#3114 )	2026-03-09 11:18:05 +01:00
Steven Palma	db8547e35d	test(cameras): skip flaky async_read test (#3106 )	2026-03-08 14:02:33 +01:00
Steven Palma	c17d949531	chore(readme): update citation with ICLR26 paper (#3107 ) * peer reviewed citation 🎉 Signed-off-by: Francesco Capuano <74058581+fracapuano@users.noreply.github.com> * add iclr year Signed-off-by: Francesco Capuano <74058581+fracapuano@users.noreply.github.com> * fix quentin's spelling name Signed-off-by: Francesco Capuano <74058581+fracapuano@users.noreply.github.com> * docs(readme): update citation --------- Signed-off-by: Francesco Capuano <74058581+fracapuano@users.noreply.github.com> Co-authored-by: Francesco Capuano <74058581+fracapuano@users.noreply.github.com>	2026-03-08 14:01:43 +01:00
Steven Palma	1e131f93f8	chore(docs): add uv installation instructions (#3105 ) * chore(docs): add uv installation instructions * fix(docs): format tabs * chore(docs): small details * chore(docs): last details uv installation instructions * chore(docs): last detail --- Co-authored-by: sahilmaniyar888 <156301258+sahilmaniyar888@users.noreply.github.com>	2026-03-08 13:00:06 +01:00
Ignat Georgiev	2fb5c7add0	feat(train): add cudnn_deterministic option for reproducible training (#3102 ) Add a `cudnn_deterministic` flag to `TrainPipelineConfig` (default: False) that sets `torch.backends.cudnn.deterministic = True` and disables benchmark mode, eliminating CUDA floating-point non-determinism at the cost of ~10-20% training speed. When False (default) the existing benchmark=True behaviour is preserved.	2026-03-08 12:29:33 +01:00
Martino Russi	4f2ef024d8	feat(robots): Unitree G1 WBC implementation (#2876 ) * move locomotion from examples to robot, move controller to teleoperator class * modify teleoperate to send back actions to robot * whole body controller * add holosoma to locomotros * various updates * update joint zeroing etc * ensure safefail with locomotion * add unitree locomotion * launch camera from g1 server * publish at varying framerates * fix async read in camera * attempting to fix camera lag * test camera speedup * training * inference works * remove logging from pi0 * remove logging * push local changes * testing * final changes * revert control_utils * revert utils * revert * revert g1 * revert again: * revert utils * push recents * remove examples * remove junk * remove mjlog * revergt edit_dataset * Update lerobot_edit_dataset.py Signed-off-by: Martino Russi <77496684+nepyope@users.noreply.github.com> * undo teleop changes * revert logging * remove loggings * remove loogs * revert dataset tools * Update dataset_tools.py Signed-off-by: Martino Russi <77496684+nepyope@users.noreply.github.com> * move gravity to utils * revert changes * remove matplotlib viewer (rerun works fine) * factory revert * send policy action directly * recent changes * implement flexible action space * send empty command if arms are missing * rename locomotion to controller * add init * implement feedback * add feedback for teleoperator * fix ruff * fix ruff * use read_latest * fix zmq camera * revert exo_serial * simplify PR * revert exo_changes * revert camera_zmq * Update camera_zmq.py Signed-off-by: Martino Russi <77496684+nepyope@users.noreply.github.com> * remove frame duplication from zmq server * revert channerfactoryinitialize * keep channelfactoryinitialize * remove zeroing out logic * fix typo * refactor teleop class * simplify teleop further * import armindex at the top * fix visualizer again * revert ik helper * push stuff * simplify image_server * update image_server * asd * add threading logic * simplify ik helper stuff * simplify holosoma * fix names * fix docs * revert leg override * clean connect * fix controller * fix ruff * clean teleoperator * set_from_wireless * avoid double initializations * refactor robot class * fix pre-commit * update docs * update docs format * add teleop instructions * unitree_g1 specific exception in record/teleoperate * add thumbnail to docs * add thumbnail to doc * refactor(unitree): multiple improvements (#3103) * refactor(unitree): multiple improvements * test(unitree): added tests + improved installation instructions * refactor(robots): minor changes unitree robot kinematic * chore(robots): rename g1 kinematics file --------- Signed-off-by: Martino Russi <77496684+nepyope@users.noreply.github.com> Signed-off-by: Steven Palma <imstevenpmwork@ieee.org> Co-authored-by: Steven Palma <imstevenpmwork@ieee.org> Co-authored-by: Steven Palma <steven.palma@huggingface.co>	2026-03-08 11:33:24 +01:00
Shun.Sasaki	6139b133ca	fix(async_inference): restore robot module imports in robot_client.py (#3081 )	2026-03-06 17:14:14 +01:00
Steven Palma	85de893fa7	fix(ci): skip HF log in (and tests) in forks and community PRs (#3097 ) * fix(ci): skip HF log in (and tests) in forks and community PRs * chore(test): remove comment about test meant to be only run locally * fix(tests): no hf log in decorator for xvla * fix(test): no decorator in yield	2026-03-06 16:33:43 +01:00
Steven Palma	a4c66e530b	chore(docs): remove pi installation note (#3095 )	2026-03-06 15:52:54 +01:00
Steven Palma	a225127527	chore(dependencies): sync intelrealsense + added notes (#3094 )	2026-03-06 10:50:46 +01:00