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feat(robots): Unitree G1 WBC implementation (#2876)

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* 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>
This commit is contained in:
Martino Russi
2026-03-08 11:33:24 +01:00
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parent 6139b133ca
commit 4f2ef024d8
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docs/source/unitree_g1.mdx
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@@ -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_