add resume

add aloha setup
add degree to aloha
2026-05-13 15:49:53 +00:00 · 2025-09-14 14:06:15 +02:00 · 2025-09-14 12:45:08 +02:00 · 2025-09-13 21:17:51 +02:00 · 2025-09-11 16:11:01 +02:00 · 2025-09-08 18:29:39 +02:00
82 changed files with 2970 additions and 194 deletions
@@ -30,7 +30,7 @@ pytest -sx tests/test_stuff.py::test_something
 ```

 ```bash
-python -m lerobot.scripts.train --some.option=true
+lerobot-train --some.option=true
 ```

 ## SECTION TO REMOVE BEFORE SUBMITTING YOUR PR
@@ -29,8 +29,8 @@ on:
 env:
  UV_VERSION: "0.8.0"
  PYTHON_VERSION: "3.10"
-  DOCKER_IMAGE_NAME_CPU: huggingface/lerobot-gpu:latest
-  DOCKER_IMAGE_NAME_GPU: huggingface/lerobot-cpu:latest
+  DOCKER_IMAGE_NAME_CPU: huggingface/lerobot-cpu:latest
+  DOCKER_IMAGE_NAME_GPU: huggingface/lerobot-gpu:latest

 # Ensures that only the latest commit is built, canceling older runs.
 concurrency:
@@ -44,7 +44,7 @@ test-end-to-end:
 	${MAKE} DEVICE=$(DEVICE) test-smolvla-ete-eval

 test-act-ete-train:
-	python -m lerobot.scripts.train \
+	lerobot-train \
 		--policy.type=act \
 		--policy.dim_model=64 \
 		--policy.n_action_steps=20 \
@@ -68,12 +68,12 @@ test-act-ete-train:
 		--output_dir=tests/outputs/act/

 test-act-ete-train-resume:
-	python -m lerobot.scripts.train \
+	lerobot-train \
 		--config_path=tests/outputs/act/checkpoints/000002/pretrained_model/train_config.json \
 		--resume=true

 test-act-ete-eval:
-	python -m lerobot.scripts.eval \
+	lerobot-eval \
 		--policy.path=tests/outputs/act/checkpoints/000004/pretrained_model \
 		--policy.device=$(DEVICE) \
 		--env.type=aloha \
@@ -82,7 +82,7 @@ test-act-ete-eval:
 		--eval.batch_size=1

 test-diffusion-ete-train:
-	python -m lerobot.scripts.train \
+	lerobot-train \
 		--policy.type=diffusion \
 		--policy.down_dims='[64,128,256]' \
 		--policy.diffusion_step_embed_dim=32 \
@@ -106,7 +106,7 @@ test-diffusion-ete-train:
 		--output_dir=tests/outputs/diffusion/

 test-diffusion-ete-eval:
-	python -m lerobot.scripts.eval \
+	lerobot-eval \
 		--policy.path=tests/outputs/diffusion/checkpoints/000002/pretrained_model \
 		--policy.device=$(DEVICE) \
 		--env.type=pusht \
@@ -115,7 +115,7 @@ test-diffusion-ete-eval:
 		--eval.batch_size=1

 test-tdmpc-ete-train:
-	python -m lerobot.scripts.train \
+	lerobot-train \
 		--policy.type=tdmpc \
 		--policy.device=$(DEVICE) \
 		--policy.push_to_hub=false \
@@ -137,7 +137,7 @@ test-tdmpc-ete-train:
 		--output_dir=tests/outputs/tdmpc/

 test-tdmpc-ete-eval:
-	python -m lerobot.scripts.eval \
+	lerobot-eval \
 		--policy.path=tests/outputs/tdmpc/checkpoints/000002/pretrained_model \
 		--policy.device=$(DEVICE) \
 		--env.type=xarm \
@@ -148,7 +148,7 @@ test-tdmpc-ete-eval:


 test-smolvla-ete-train:
-	python -m lerobot.scripts.train \
+	lerobot-train \
 		--policy.type=smolvla \
 		--policy.n_action_steps=20 \
 		--policy.chunk_size=20 \
@@ -171,7 +171,7 @@ test-smolvla-ete-train:
 		--output_dir=tests/outputs/smolvla/

 test-smolvla-ete-eval:
-	python -m lerobot.scripts.eval \
+	lerobot-eval \
 		--policy.path=tests/outputs/smolvla/checkpoints/000004/pretrained_model \
 		--policy.device=$(DEVICE) \
 		--env.type=aloha \
@@ -6,7 +6,7 @@

 <div align="center">

-[![Tests](https://github.com/huggingface/lerobot/actions/workflows/nightly.yml/badge.svg?branch=main)](https://github.com/huggingface/lerobot/actions/workflows/nighty.yml?query=branch%3Amain)
+[![Tests](https://github.com/huggingface/lerobot/actions/workflows/nightly.yml/badge.svg?branch=main)](https://github.com/huggingface/lerobot/actions/workflows/nightly.yml?query=branch%3Amain)
 [![Python versions](https://img.shields.io/pypi/pyversions/lerobot)](https://www.python.org/downloads/)
 [![License](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](https://github.com/huggingface/lerobot/blob/main/LICENSE)
 [![Status](https://img.shields.io/pypi/status/lerobot)](https://pypi.org/project/lerobot/)
@@ -276,7 +276,7 @@ Check out [example 2](https://github.com/huggingface/lerobot/blob/main/examples/
 We also provide a more capable script to parallelize the evaluation over multiple environments during the same rollout. Here is an example with a pretrained model hosted on [lerobot/diffusion_pusht](https://huggingface.co/lerobot/diffusion_pusht):

 ```bash
-python -m lerobot.scripts.eval \
+lerobot-eval \
    --policy.path=lerobot/diffusion_pusht \
    --env.type=pusht \
    --eval.batch_size=10 \
@@ -288,10 +288,10 @@ python -m lerobot.scripts.eval \
 Note: After training your own policy, you can re-evaluate the checkpoints with:

 ```bash
-python -m lerobot.scripts.eval --policy.path={OUTPUT_DIR}/checkpoints/last/pretrained_model
+lerobot-eval --policy.path={OUTPUT_DIR}/checkpoints/last/pretrained_model
 ```

-See `python -m lerobot.scripts.eval --help` for more instructions.
+See `lerobot-eval --help` for more instructions.

 ### Train your own policy

@@ -303,7 +303,7 @@ A link to the wandb logs for the run will also show up in yellow in your termina

 \<img src="https://raw.githubusercontent.com/huggingface/lerobot/main/media/wandb.png" alt="WandB logs example"\>

-Note: For efficiency, during training every checkpoint is evaluated on a low number of episodes. You may use `--eval.n_episodes=500` to evaluate on more episodes than the default. Or, after training, you may want to re-evaluate your best checkpoints on more episodes or change the evaluation settings. See `python -m lerobot.scripts.eval --help` for more instructions.
+Note: For efficiency, during training every checkpoint is evaluated on a low number of episodes. You may use `--eval.n_episodes=500` to evaluate on more episodes than the default. Or, after training, you may want to re-evaluate your best checkpoints on more episodes or change the evaluation settings. See `lerobot-eval --help` for more instructions.

 #### Reproduce state-of-the-art (SOTA)

@@ -311,7 +311,7 @@ We provide some pretrained policies on our [hub page](https://huggingface.co/ler
 You can reproduce their training by loading the config from their run. Simply running:

 ```bash
-python -m lerobot.scripts.train --config_path=lerobot/diffusion_pusht
+lerobot-train --config_path=lerobot/diffusion_pusht
 ```

 reproduces SOTA results for Diffusion Policy on the PushT task.
@@ -29,7 +29,7 @@ ENV DEBIAN_FRONTEND=noninteractive \

 # Install system dependencies and uv (as root)
 RUN apt-get update && apt-get install -y --no-install-recommends \
-    build-essential git curl libglib2.0-0 libegl1-mesa ffmpeg \
+    build-essential git curl libglib2.0-0 libegl1-mesa-dev ffmpeg \
    libusb-1.0-0-dev speech-dispatcher libgeos-dev portaudio19-dev \
    && curl -LsSf https://astral.sh/uv/install.sh | sh \
    && mv /root/.local/bin/uv /usr/local/bin/uv \
@@ -35,10 +35,14 @@
    title: Koch v1.1
  - local: lekiwi
    title: LeKiwi
+  - local: reachy2
+    title: Reachy 2
  title: "Robots"
 - sections:
  - local: notebooks
    title: Notebooks
+  - local: feetech
+    title: Updating Feetech Firmware
  title: "Resources"
 - sections:
  - local: contributing
@@ -9,7 +9,7 @@ To instantiate a camera, you need a camera identifier. This identifier might cha
 To find the camera indices of the cameras plugged into your system, run the following script:

 ```bash
-python -m lerobot.find_cameras opencv # or realsense for Intel Realsense cameras
+lerobot-find-cameras opencv # or realsense for Intel Realsense cameras
 ```

 The output will look something like this if you have two cameras connected:
@@ -0,0 +1,71 @@
+# Feetech Motor Firmware Update
+
+This tutorial guides you through updating the firmware of Feetech motors using the official Feetech software.
+
+## Prerequisites
+
+- Windows computer (Feetech software is only available for Windows)
+- Feetech motor control board
+- USB cable to connect the control board to your computer
+- Feetech motors connected to the control board
+
+## Step 1: Download Feetech Software
+
+1. Visit the official Feetech software download page: [https://www.feetechrc.com/software.html](https://www.feetechrc.com/software.html)
+2. Download the latest version of the Feetech debugging software (FD)
+3. Install the software on your Windows computer
+
+## Step 2: Hardware Setup
+
+1. Connect your Feetech motors to the motor control board
+2. Connect the motor control board to your Windows computer via USB cable
+3. Ensure power is supplied to the motors
+
+## Step 3: Configure Connection
+
+1. Launch the Feetech debugging software
+2. Select the correct COM port from the port dropdown menu
+   - If unsure which port to use, check Windows Device Manager under "Ports (COM & LPT)"
+3. Set the appropriate baud rate (typically 1000000 for most Feetech motors)
+4. Click "Open" to establish communication with the control board
+
+## Step 4: Scan for Motors
+
+1. Once connected, click the "Search" button to detect all connected motors
+2. The software will automatically discover and list all motors on the bus
+3. Each motor will appear with its ID number
+
+## Step 5: Update Firmware
+
+For each motor you want to update:
+
+1. **Select the motor** from the list by clicking on it
+2. **Click on Upgrade tab**:
+3. **Click on Online button**:
+   - If an potential firmware update is found, it will be displayed in the box
+4. **Click on Upgrade button**:
+   - The update progress will be displayed
+
+## Step 6: Verify Update
+
+1. After the update completes, the software should automatically refresh the motor information
+2. Verify that the firmware version has been updated to the expected version
+
+## Important Notes
+
+⚠️ **Warning**: Do not disconnect power or USB during firmware updates, it will potentially brick the motor.
+
+## Bonus: Motor Debugging on Linux/macOS
+
+For debugging purposes only, you can use the open-source Feetech Debug Tool:
+
+- **Repository**: [FT_SCServo_Debug_Qt](https://github.com/CarolinePascal/FT_SCServo_Debug_Qt/tree/fix/port-search-timer)
+
+### Installation Instructions
+
+Follow the instructions in the repository to install the tool, for Ubuntu you can directly install it, for MacOS you need to build it from source.
+
+**Limitations:**
+
+- This tool is for debugging and parameter adjustment only
+- Firmware updates must still be done on Windows with official Feetech software
@@ -412,7 +412,7 @@ Example configuration for training the [reward classifier](https://huggingface.c
 To train the classifier, use the `train.py` script with your configuration:

 ```bash
-python -m lerobot.scripts.train --config_path path/to/reward_classifier_train_config.json
+lerobot-train --config_path path/to/reward_classifier_train_config.json
 ```

 **Deploying and Testing the Model**
@@ -458,7 +458,7 @@ The reward classifier will automatically provide rewards based on the visual inp
 3. **Train the classifier**:

   ```bash
-   python -m lerobot.scripts.train --config_path src/lerobot/configs/reward_classifier_train_config.json
+   lerobot-train --config_path src/lerobot/configs/reward_classifier_train_config.json
   ```

 4. **Test the classifier**:
@@ -19,7 +19,7 @@ pip install -e ".[hopejr]"
 Before starting calibration and operation, you need to identify the USB ports for each HopeJR component. Run this script to find the USB ports for the arm, hand, glove, and exoskeleton:

 ```bash
-python -m lerobot.find_port
+lerobot-find-port
 ```

 This will display the available USB ports and their associated devices. Make note of the port paths (e.g., `/dev/tty.usbmodem58760433331`, `/dev/tty.usbmodem11301`) as you'll need to specify them in the `--robot.port` and `--teleop.port` parameters when recording data, replaying episodes, or running teleoperation scripts.
@@ -31,7 +31,7 @@ Before performing teleoperation, HopeJR's limbs need to be calibrated. Calibrati
 ### 1.1 Calibrate Robot Hand

 ```bash
-python -m lerobot.calibrate \
+lerobot-calibrate \
    --robot.type=hope_jr_hand \
    --robot.port=/dev/tty.usbmodem58760432281 \
    --robot.id=blue \
@@ -81,7 +81,7 @@ Once you have set the appropriate boundaries for all joints, click "Save" to sav
 ### 1.2 Calibrate Teleoperator Glove

 ```bash
-python -m lerobot.calibrate \
+lerobot-calibrate \
    --teleop.type=homunculus_glove \
    --teleop.port=/dev/tty.usbmodem11201 \
    --teleop.id=red \
@@ -120,7 +120,7 @@ Once calibration is complete, the system will save the calibration to `/Users/yo
 ### 1.3 Calibrate Robot Arm

 ```bash
-python -m lerobot.calibrate \
+lerobot-calibrate \
    --robot.type=hope_jr_arm \
    --robot.port=/dev/tty.usbserial-1110 \
    --robot.id=white
@@ -146,7 +146,7 @@ Use the calibration interface to set the range boundaries for each joint. Move e
 ### 1.4 Calibrate Teleoperator Exoskeleton

 ```bash
-python -m lerobot.calibrate \
+lerobot-calibrate \
    --teleop.type=homunculus_arm \
    --teleop.port=/dev/tty.usbmodem11201 \
    --teleop.id=black
@@ -178,7 +178,7 @@ Due to global variable conflicts in the Feetech middleware, teleoperation for ar
 ### Hand

 ```bash
-python -m lerobot.teleoperate \
+lerobot-teleoperate \
    --robot.type=hope_jr_hand \
    --robot.port=/dev/tty.usbmodem58760432281 \
    --robot.id=blue \
@@ -194,7 +194,7 @@ python -m lerobot.teleoperate \
 ### Arm

 ```bash
-python -m lerobot.teleoperate \
+lerobot-teleoperate \
    --robot.type=hope_jr_arm \
    --robot.port=/dev/tty.usbserial-1110 \
    --robot.id=white \
@@ -214,7 +214,7 @@ Record, Replay and Train with Hope-JR is still experimental.
 This step records the dataset, which can be seen as an example [here](https://huggingface.co/datasets/nepyope/hand_record_test_with_video_data/settings).

 ```bash
-python -m lerobot.record \
+lerobot-record \
    --robot.type=hope_jr_hand \
    --robot.port=/dev/tty.usbmodem58760432281 \
    --robot.id=right \
@@ -236,7 +236,7 @@ python -m lerobot.record \
 ### Replay

 ```bash
-python -m lerobot.replay \
+lerobot-replay \
    --robot.type=hope_jr_hand \
    --robot.port=/dev/tty.usbmodem58760432281 \
    --robot.id=right \
@@ -248,7 +248,7 @@ python -m lerobot.replay \
 ### Train

 ```bash
-python -m lerobot.scripts.train \
+lerobot-train \
  --dataset.repo_id=nepyope/hand_record_test_with_video_data \
  --policy.type=act \
  --output_dir=outputs/train/hopejr_hand \
@@ -263,7 +263,7 @@ python -m lerobot.scripts.train \
 This training run can be viewed as an example [here](https://wandb.ai/tino/lerobot/runs/rp0k8zvw?nw=nwusertino).

 ```bash
-python -m lerobot.record \
+lerobot-record \
  --robot.type=hope_jr_hand \
  --robot.port=/dev/tty.usbmodem58760432281 \
  --robot.id=right \
@@ -45,7 +45,7 @@ Note that the `id` associated with a robot is used to store the calibration file
 <hfoptions id="teleoperate_so101">
 <hfoption id="Command">
 ```bash
-python -m lerobot.teleoperate \
+lerobot-teleoperate \
    --robot.type=so101_follower \
    --robot.port=/dev/tty.usbmodem58760431541 \
    --robot.id=my_awesome_follower_arm \
@@ -101,7 +101,7 @@ With `rerun`, you can teleoperate again while simultaneously visualizing the cam
 <hfoptions id="teleoperate_koch_camera">
 <hfoption id="Command">
 ```bash
-python -m lerobot.teleoperate \
+lerobot-teleoperate \
    --robot.type=koch_follower \
    --robot.port=/dev/tty.usbmodem58760431541 \
    --robot.id=my_awesome_follower_arm \
@@ -174,7 +174,7 @@ Now you can record a dataset. To record 5 episodes and upload your dataset to th
 <hfoptions id="record">
 <hfoption id="Command">
 ```bash
-python -m lerobot.record \
+lerobot-record \
    --robot.type=so101_follower \
    --robot.port=/dev/tty.usbmodem585A0076841 \
    --robot.id=my_awesome_follower_arm \
@@ -376,7 +376,7 @@ You can replay the first episode on your robot with either the command below or
 <hfoptions id="replay">
 <hfoption id="Command">
 ```bash
-python -m lerobot.replay \
+lerobot-replay \
    --robot.type=so101_follower \
    --robot.port=/dev/tty.usbmodem58760431541 \
    --robot.id=my_awesome_follower_arm \
@@ -428,10 +428,10 @@ Your robot should replicate movements similar to those you recorded. For example

 ## Train a policy

-To train a policy to control your robot, use the [`python -m lerobot.scripts.train`](https://github.com/huggingface/lerobot/blob/main/src/lerobot/scripts/train.py) script. A few arguments are required. Here is an example command:
+To train a policy to control your robot, use the [`lerobot-train`](https://github.com/huggingface/lerobot/blob/main/src/lerobot/scripts/train.py) script. A few arguments are required. Here is an example command:

 ```bash
-python -m lerobot.scripts.train \
+lerobot-train \
  --dataset.repo_id=${HF_USER}/so101_test \
  --policy.type=act \
  --output_dir=outputs/train/act_so101_test \
@@ -453,7 +453,7 @@ Training should take several hours. You will find checkpoints in `outputs/train/
 To resume training from a checkpoint, below is an example command to resume from `last` checkpoint of the `act_so101_test` policy:

 ```bash
-python -m lerobot.scripts.train \
+lerobot-train \
  --config_path=outputs/train/act_so101_test/checkpoints/last/pretrained_model/train_config.json \
  --resume=true
 ```
@@ -490,7 +490,7 @@ You can use the `record` script from [`lerobot/record.py`](https://github.com/hu
 <hfoptions id="eval">
 <hfoption id="Command">
 ```bash
-python -m lerobot.record  \
+lerobot-record  \
  --robot.type=so100_follower \
  --robot.port=/dev/ttyACM1 \
  --robot.cameras="{ up: {type: opencv, index_or_path: /dev/video10, width: 640, height: 480, fps: 30}, side: {type: intelrealsense, serial_number_or_name: 233522074606, width: 640, height: 480, fps: 30}}" \
@@ -96,10 +96,10 @@ If you uploaded your dataset to the hub you can [visualize your dataset online](

 ## Train a policy

-To train a policy to control your robot, use the [`python -m lerobot.scripts.train`](https://github.com/huggingface/lerobot/blob/main/src/lerobot/scripts/train.py) script. A few arguments are required. Here is an example command:
+To train a policy to control your robot, use the [`lerobot-train`](https://github.com/huggingface/lerobot/blob/main/src/lerobot/scripts/train.py) script. A few arguments are required. Here is an example command:

 ```bash
-python -m lerobot.scripts.train \
+lerobot-train \
  --dataset.repo_id=${HF_USER}/il_gym \
  --policy.type=act \
  --output_dir=outputs/train/il_sim_test \
@@ -31,7 +31,7 @@ pip install -e ".[dynamixel]"
 To find the port for each bus servo adapter, run this script:

 ```bash
-python -m lerobot.find_port
+lerobot-find-port
 ```

 <hfoptions id="example">
@@ -98,7 +98,7 @@ For a visual reference on how to set the motor ids please refer to [this video](
 <hfoption id="Command">

 ```bash
-python -m lerobot.setup_motors \
+lerobot-setup-motors \
    --robot.type=koch_follower \
    --robot.port=/dev/tty.usbmodem575E0031751 # <- paste here the port found at previous step
 ```
@@ -174,7 +174,7 @@ Do the same steps for the leader arm but modify the command or script accordingl
 <hfoption id="Command">

 ```bash
-python -m lerobot.setup_motors \
+lerobot-setup-motors \
    --teleop.type=koch_leader \
    --teleop.port=/dev/tty.usbmodem575E0031751 \  # <- paste here the port found at previous step
 ```
@@ -211,7 +211,7 @@ Run the following command or API example to calibrate the follower arm:
 <hfoption id="Command">

 ```bash
-python -m lerobot.calibrate \
+lerobot-calibrate \
    --robot.type=koch_follower \
    --robot.port=/dev/tty.usbmodem58760431551 \ # <- The port of your robot
    --robot.id=my_awesome_follower_arm  # <- Give the robot a unique name
@@ -249,7 +249,7 @@ Do the same steps to calibrate the leader arm, run the following command or API
 <hfoption id="Command">

 ```bash
-python -m lerobot.calibrate \
+lerobot-calibrate \
    --teleop.type=koch_leader \
    --teleop.port=/dev/tty.usbmodem58760431551 \ # <- The port of your robot
    --teleop.id=my_awesome_leader_arm  # <- Give the robot a unique name
@@ -60,7 +60,7 @@ First, we will assemble the two SO100/SO101 arms. One to attach to the mobile ba
 To find the port for each bus servo adapter, run this script:

 ```bash
-python -m lerobot.find_port
+lerobot-find-port
 ```

 <hfoptions id="example">
@@ -116,7 +116,7 @@ The instructions for configuring the motors can be found in the SO101 [docs](./s
 You can run this command to setup motors for LeKiwi. It will first setup the motors for arm (id 6..1) and then setup motors for wheels (9,8,7)

 ```bash
-python -m lerobot.setup_motors \
+lerobot-setup-motors \
    --robot.type=lekiwi \
    --robot.port=/dev/tty.usbmodem58760431551 # <- paste here the port found at previous step
 ```
@@ -174,7 +174,7 @@ The calibration process is very important because it allows a neural network tra
 Make sure the arm is connected to the Raspberry Pi and run this script or API example (on the Raspberry Pi via SSH) to launch calibration of the follower arm:

 ```bash
-python -m lerobot.calibrate \
+lerobot-calibrate \
    --robot.type=lekiwi \
    --robot.id=my_awesome_kiwi # <- Give the robot a unique name
 ```
@@ -193,7 +193,7 @@ Then, to calibrate the leader arm (which is attached to the laptop/pc). Run the
 <hfoption id="Command">

 ```bash
-python -m lerobot.calibrate \
+lerobot-calibrate \
    --teleop.type=so100_leader \
    --teleop.port=/dev/tty.usbmodem58760431551 \ # <- The port of your robot
    --teleop.id=my_awesome_leader_arm # <- Give the robot a unique name
@@ -0,0 +1,288 @@
+# Reachy 2
+
+Reachy 2 is an open-source humanoid robot made by Pollen Robotics, specifically designed for the development of embodied AI and real-world applications.
+Check out [Pollen Robotics website](https://www.pollen-robotics.com/reachy/), or access [Reachy 2 documentation](https://docs.pollen-robotics.com/) for more information on the platform!
+
+## Teleoperate Reachy 2
+
+Currently, there are two ways to teleoperate Reachy 2:
+
+- Pollen Robotics’ VR teleoperation (not included in LeRobot).
+- Robot-to-robot teleoperation (use one Reachy 2 to control another).
+
+## Reachy 2 Simulation
+
+**(Linux only)** You can run Reachy 2 in simulation (Gazebo or MuJoCo) using the provided [Docker image](https://hub.docker.com/r/pollenrobotics/reachy2_core).
+
+1. Install [Docker Engine](https://docs.docker.com/engine/).
+2. Run (for MuJoCo):
+
+```
+docker run --rm -it \
+  --name reachy \
+  --privileged \
+  --network host \
+  --ipc host \
+  --device-cgroup-rule='c 189:* rwm' \
+  --group-add audio \
+  -e ROS_DOMAIN_ID="$ROS_DOMAIN_ID" \
+  -e DISPLAY="$DISPLAY" \
+  -e RCUTILS_CONSOLE_OUTPUT_FORMAT="[{severity}]: {message}" \
+  -e REACHY2_CORE_SERVICE_FAKE="${REACHY2_CORE_SERVICE_FAKE:-true}" \
+  -v /dev:/dev \
+  -v "$HOME/.reachy_config":/home/reachy/.reachy_config_override \
+  -v "$HOME/.reachy.log":/home/reachy/.ros/log \
+  -v /usr/lib/x86_64-linux-gnu:/opt/host-libs \
+  --entrypoint /package/launch.sh \
+  pollenrobotics/reachy2_core:1.7.5.9_deploy \
+  start_rviz:=true start_sdk_server:=true mujoco:=true
+```
+
+> If MuJoCo runs slowly (low simulation frequency), append `-e LD_LIBRARY_PATH="/opt/host-libs:$LD_LIBRARY_PATH" \` to the previous command to improve performance:
+>
+> ```
+> docker run --rm -it \
+>   --name reachy \
+>   --privileged \
+>   --network host \
+>   --ipc host \
+>   --device-cgroup-rule='c 189:* rwm' \
+>   --group-add audio \
+>   -e ROS_DOMAIN_ID="$ROS_DOMAIN_ID" \
+>   -e DISPLAY="$DISPLAY" \
+>   -e RCUTILS_CONSOLE_OUTPUT_FORMAT="[{severity}]: {message}" \
+>   -e REACHY2_CORE_SERVICE_FAKE="${REACHY2_CORE_SERVICE_FAKE:-true}" \
+>   -e LD_LIBRARY_PATH="/opt/host-libs:$LD_LIBRARY_PATH" \
+>   -v /dev:/dev \
+>   -v "$HOME/.reachy_config":/home/reachy/.reachy_config_override \
+>   -v "$HOME/.reachy.log":/home/reachy/.ros/log \
+>   -v /usr/lib/x86_64-linux-gnu:/opt/host-libs \
+>   --entrypoint /package/launch.sh \
+>   pollenrobotics/reachy2_core:1.7.5.9_deploy \
+>   start_rviz:=true start_sdk_server:=true mujoco:=true
+> ```
+
+## Setup
+
+### Prerequisites
+
+- On your robot, check the **service images** meet the minimum versions:
+  - **reachy2-core >= 1.7.5.2**
+  - **webrtc >= 2.0.1.1**
+
+Then, if you want to use VR teleoperation:
+
+- Install the [Reachy 2 teleoperation application](https://docs.pollen-robotics.com/teleoperation/teleoperation-introduction/discover-teleoperation/).
+  Use version **>=v1.2.0**
+
+We recommend using two computers: one for teleoperation (Windows required) and another for recording with LeRobot.
+
+### Install LeRobot
+
+Follow the [installation instructions](https://github.com/huggingface/lerobot#installation) to install LeRobot.
+
+Install LeRobot with Reachy 2 dependencies:
+
+```bash
+pip install -e ".[reachy2]"
+```
+
+### (Optional but recommended) Install pollen_data_acquisition_server
+
+How you manage Reachy 2 recording sessions is up to you, but the **easiest** way is to use this server so you can control sessions directly from the VR teleoperation app.
+
+> **Note:** Currently, only the VR teleoperation application works as a client for this server, so this step primarily targets teleoperation. You’re free to develop custom clients to manage sessions to your needs.
+
+In your LeRobot environment, install the server from source:
+
+```bash
+git clone https://github.com/pollen-robotics/pollen_data_acquisition_server.git
+cd pollen_data_acquisition_server
+pip install -e .
+```
+
+Find the [pollen_data_acquisition_server documentation here](https://github.com/pollen-robotics/pollen_data_acquisition_server).
+
+## Step 1: Recording
+
+### Get Reachy 2 IP address
+
+Before starting teleoperation and data recording, find the [robot's IP address](https://docs.pollen-robotics.com/getting-started/setup-reachy2/connect-reachy2/).
+We strongly recommend connecting all devices (PC and robot) via **Ethernet**.
+
+### Launch recording
+
+There are two ways to manage recording sessions when using the Reachy 2 VR teleoperation application:
+
+- **Using the data acquisition server (recommended for VR teleop)**: The VR app orchestrates sessions (via the server it tells LeRobot when to create datasets, start/stop episodes) while also controlling the robot’s motions.
+- **Using LeRobot’s record script**: LeRobot owns session control and decides when to start/stop episodes. If you also use the VR teleop app, it’s only for motion control.
+
+### Option 1: Using Pollen data acquisition server (recommended for VR teleop)
+
+Make sure you have installed pollen_data_acquisition_server, as explained in the Setup section.
+
+Launch the data acquisition server to be able to manage your session directly from the teleoperation application:
+
+```bash
+python -m pollen_data_acquisition_server.server
+```
+
+Then get into the teleoperation application and choose "Data acquisition session".
+You can finally setup your session by following the screens displayed.
+
+> Even without the VR app, you can use the `pollen_data_acquisition_server` with your own client implementation.
+
+### Option 2: Using lerobot.record
+
+Reachy 2 is fully supported by LeRobot’s recording features.
+If you choose this option but still want to use the VR teleoperation application, select "Standard session" in the app.
+
+**Example: start a recording without the mobile base:**
+First add reachy2 and reachy2_teleoperator to the imports of the record script. Then you can use the following command:
+
+```bash
+python -m lerobot.record \
+    --robot.type=reachy2 \
+    --robot.ip_address=192.168.0.200 \
+    --robot.id=r2-0000 \
+    --robot.use_external_commands=true \
+    --robot.with_mobile_base=false \
+    --teleop.type=reachy2_teleoperator \
+    --teleop.ip_address=192.168.0.200 \
+    --teleop.with_mobile_base=false \
+    --dataset.repo_id=pollen_robotics/record_test \
+    --dataset.single_task="Reachy 2 recording test" \
+    --dataset.num_episodes=1 \
+    --dataset.episode_time_s=5 \
+    --dataset.fps=15 \
+    --dataset.push_to_hub=true \
+    --dataset.private=true \
+    --display_data=true
+```
+
+#### Specific Options
+
+**Extended setup overview (all options included):**
+
+```bash
+python -m lerobot.record \
+    --robot.type=reachy2 \
+    --robot.ip_address=192.168.0.200 \
+    --robot.use_external_commands=true \
+    --robot.with_mobile_base=true \
+    --robot.with_l_arm=true \
+    --robot.with_r_arm=true \
+    --robot.with_neck=true \
+    --robot.with_antennas=true \
+    --robot.with_left_teleop_camera=true \
+    --robot.with_right_teleop_camera=true \
+    --robot.with_torso_camera=false \
+    --robot.disable_torque_on_disconnect=false \
+    --robot.max_relative_target=5.0 \
+    --teleop.type=reachy2_teleoperator \
+    --teleop.ip_address=192.168.0.200 \
+    --teleop.use_present_position=false \
+    --teleop.with_mobile_base=false \
+    --teleop.with_l_arm=true \
+    --teleop.with_r_arm=true \
+    --teleop.with_neck=true \
+    --teleop.with_antennas=true \
+    --dataset.repo_id=pollen_robotics/record_test \
+    --dataset.single_task="Reachy 2 recording test" \
+    --dataset.num_episodes=1 \
+    --dataset.episode_time_s=5 \
+    --dataset.fps=15 \
+    --dataset.push_to_hub=true \
+    --dataset.private=true \
+    --display_data=true
+```
+
+##### `--robot.use_external_commands`
+
+Determine whether LeRobot robot.send_action() sends commands to the robot.
+**Must** be set to false while using the VR teleoperation application, as the app already sends commands.
+
+##### `--teleop.use_present_position`
+
+Determine whether the teleoperator reads the goal or present position of the robot.
+Must be set to true if a compliant Reachy 2 is used to control another one.
+
+##### Use the relevant parts
+
+From our initial tests, recording **all** joints when only some are moving can reduce model quality with certain policies.
+To avoid this, you can exclude specific parts from recording and replay using:
+
+````
+--robot.with_<part>=false
+```,
+with `<part>` being one of : `mobile_base`, `l_arm`, `r_arm", `neck`, `antennas`.
+It determine whether the corresponding part is recorded in the observations. True if not set.
+
+By default, **all parts are recorded**.
+
+The same per-part mechanism is available in `reachy2_teleoperator` as well.
+
+````
+
+--teleop.with\_<part>
+
+```
+with `<part>` being one of : `mobile_base`, `l_arm`, `r_arm", `neck`, `antennas`.
+Determine whether the corresponding part is recorded in the actions. True if not set.
+
+> **Important:** In a given session, the **enabled parts must match** on both the robot and the teleoperator.
+For example, if the robot runs with `--robot.with_mobile_base=false`, the teleoperator must disable the same part `--teleoperator.with_mobile_base=false`.
+
+##### Use the relevant cameras
+
+You can do the same for **cameras**. By default, only the **teleoperation cameras** are recorded (both `left_teleop_camera` and `right_teleop_camera`). Enable or disable each camera with:
+
+```
+
+--robot.with_left_teleop_camera=<true|false>
+--robot.with_right_teleop_camera=<true|false>
+--robot.with_torso_camera=<true|false>
+
+````
+
+
+## Step 2: Replay
+
+Make sure the robot is configured with the same parts as the dataset:
+
+```bash
+python -m lerobot.replay \
+    --robot.type=reachy2 \
+    --robot.ip_address=192.168.0.200 \
+    --robot.use_external_commands=false \
+    --robot.with_mobile_base=false \
+    --dataset.repo_id=pollen_robotics/record_test \
+    --dataset.episode=0
+    --display_data=true
+````
+
+## Step 3: Train
+
+```bash
+python -m lerobot.scripts.train \
+  --dataset.repo_id=pollen_robotics/record_test \
+  --policy.type=act \
+  --output_dir=outputs/train/reachy2_test \
+  --job_name=reachy2 \
+  --policy.device=mps \
+  --wandb.enable=true \
+  --policy.repo_id=pollen_robotics/record_test_policy
+```
+
+## Step 4: Evaluate
+
+```bash
+python -m lerobot.record \
+  --robot.type=reachy2 \
+  --robot.ip_address=192.168.0.200 \
+  --display_data=false \
+  --dataset.repo_id=pollen_robotics/eval_record_test \
+  --dataset.single_task="Evaluate reachy2 policy" \
+  --dataset.num_episodes=10 \
+  --policy.path=outputs/train/reachy2_test/checkpoints/last/pretrained_model
+```
@@ -54,7 +54,7 @@ If you don't have a gpu device, you can train using our notebook on [![Google Co
 Pass your dataset to the training script using `--dataset.repo_id`. If you want to test your installation, run the following command where we use one of the datasets we collected for the [SmolVLA Paper](https://huggingface.co/papers/2506.01844).

 ```bash
-cd lerobot && python -m lerobot.scripts.train \
+cd lerobot && lerobot-train \
  --policy.path=lerobot/smolvla_base \
  --dataset.repo_id=${HF_USER}/mydataset \
  --batch_size=64 \
@@ -73,7 +73,7 @@ cd lerobot && python -m lerobot.scripts.train \
 Fine-tuning is an art. For a complete overview of the options for finetuning, run

 ```bash
-python -m lerobot.scripts.train --help
+lerobot-train --help
 ```

 <p align="center">
@@ -97,7 +97,7 @@ Similarly for when recording an episode, it is recommended that you are logged i
 Once you are logged in, you can run inference in your setup by doing:

 ```bash
-python -m lerobot.record \
+lerobot-record \
  --robot.type=so101_follower \
  --robot.port=/dev/ttyACM0 \ # <- Use your port
  --robot.id=my_blue_follower_arm \ # <- Use your robot id
@@ -26,7 +26,7 @@ Unlike the SO-101, the motor connectors are not easily accessible once the arm i
 To find the port for each bus servo adapter, run this script:

 ```bash
-python -m lerobot.find_port
+lerobot-find-port
 ```

 <hfoptions id="example">
@@ -93,7 +93,7 @@ For a visual reference on how to set the motor ids please refer to [this video](
 <hfoption id="Command">

 ```bash
-python -m lerobot.setup_motors \
+lerobot-setup-motors \
    --robot.type=so100_follower \
    --robot.port=/dev/tty.usbmodem585A0076841  # <- paste here the port found at previous step
 ```
@@ -168,7 +168,7 @@ Do the same steps for the leader arm.
 <hfoptions id="setup_motors">
 <hfoption id="Command">
 ```bash
-python -m lerobot.setup_motors \
+lerobot-setup-motors \
    --teleop.type=so100_leader \
    --teleop.port=/dev/tty.usbmodem575E0031751  # <- paste here the port found at previous step
 ```
@@ -568,7 +568,7 @@ Run the following command or API example to calibrate the follower arm:
 <hfoption id="Command">

 ```bash
-python -m lerobot.calibrate \
+lerobot-calibrate \
    --robot.type=so100_follower \
    --robot.port=/dev/tty.usbmodem58760431551 \ # <- The port of your robot
    --robot.id=my_awesome_follower_arm # <- Give the robot a unique name
@@ -606,7 +606,7 @@ Do the same steps to calibrate the leader arm, run the following command or API
 <hfoption id="Command">

 ```bash
-python -m lerobot.calibrate \
+lerobot-calibrate \
    --teleop.type=so100_leader \
    --teleop.port=/dev/tty.usbmodem58760431551 \ # <- The port of your robot
    --teleop.id=my_awesome_leader_arm # <- Give the robot a unique name
@@ -162,7 +162,7 @@ It is advisable to install one 3-pin cable in the motor after placing them befor
 To find the port for each bus servo adapter, connect MotorBus to your computer via USB and power. Run the following script and disconnect the MotorBus when prompted:

 ```bash
-python -m lerobot.find_port
+lerobot-find-port
 ```

 <hfoptions id="example">
@@ -240,7 +240,7 @@ Connect the usb cable from your computer and the power supply to the follower ar
 <hfoption id="Command">

 ```bash
-python -m lerobot.setup_motors \
+lerobot-setup-motors \
    --robot.type=so101_follower \
    --robot.port=/dev/tty.usbmodem585A0076841  # <- paste here the port found at previous step
 ```
@@ -316,7 +316,7 @@ Do the same steps for the leader arm.
 <hfoption id="Command">

 ```bash
-python -m lerobot.setup_motors \
+lerobot-setup-motors \
    --teleop.type=so101_leader \
    --teleop.port=/dev/tty.usbmodem575E0031751  # <- paste here the port found at previous step
 ```
@@ -353,7 +353,7 @@ Run the following command or API example to calibrate the follower arm:
 <hfoption id="Command">

 ```bash
-python -m lerobot.calibrate \
+lerobot-calibrate \
    --robot.type=so101_follower \
    --robot.port=/dev/tty.usbmodem58760431551 \ # <- The port of your robot
    --robot.id=my_awesome_follower_arm # <- Give the robot a unique name
@@ -402,7 +402,7 @@ Do the same steps to calibrate the leader arm, run the following command or API
 <hfoption id="Command">

 ```bash
-python -m lerobot.calibrate \
+lerobot-calibrate \
    --teleop.type=so101_leader \
    --teleop.port=/dev/tty.usbmodem58760431551 \ # <- The port of your robot
    --teleop.id=my_awesome_leader_arm # <- Give the robot a unique name
@@ -62,7 +62,7 @@ By default, every field takes its default value specified in the dataclass. If a
 Let's say that we want to train [Diffusion Policy](../src/lerobot/policies/diffusion) on the [pusht](https://huggingface.co/datasets/lerobot/pusht) dataset, using the [gym_pusht](https://github.com/huggingface/gym-pusht) environment for evaluation. The command to do so would look like this:

 ```bash
-python -m lerobot.scripts.train \
+lerobot-train \
    --dataset.repo_id=lerobot/pusht \
    --policy.type=diffusion \
    --env.type=pusht
@@ -77,7 +77,7 @@ Let's break this down:
 Let's see another example. Let's say you've been training [ACT](../src/lerobot/policies/act) on [lerobot/aloha_sim_insertion_human](https://huggingface.co/datasets/lerobot/aloha_sim_insertion_human) using the [gym-aloha](https://github.com/huggingface/gym-aloha) environment for evaluation with:

 ```bash
-python -m lerobot.scripts.train \
+lerobot-train \
    --policy.type=act \
    --dataset.repo_id=lerobot/aloha_sim_insertion_human \
    --env.type=aloha \
@@ -90,7 +90,7 @@ We now want to train a different policy for aloha on another task. We'll change
 Looking at the [`AlohaEnv`](../src/lerobot/envs/configs.py) config, the task is `"AlohaInsertion-v0"` by default, which corresponds to the task we trained on in the command above. The [gym-aloha](https://github.com/huggingface/gym-aloha?tab=readme-ov-file#description) environment also has the `AlohaTransferCube-v0` task which corresponds to this other task we want to train on. Putting this together, we can train this new policy on this different task using:

 ```bash
-python -m lerobot.scripts.train \
+lerobot-train \
    --policy.type=act \
    --dataset.repo_id=lerobot/aloha_sim_transfer_cube_human \
    --env.type=aloha \
@@ -127,7 +127,7 @@ Now, let's assume that we want to reproduce the run just above. That run has pro
 We can then simply load the config values from this file using:

 ```bash
-python -m lerobot.scripts.train \
+lerobot-train \
    --config_path=outputs/train/act_aloha_transfer/checkpoints/last/pretrained_model/ \
    --output_dir=outputs/train/act_aloha_transfer_2
 ```
@@ -137,7 +137,7 @@ python -m lerobot.scripts.train \
 Similarly to Hydra, we can still override some parameters in the CLI if we want to, e.g.:

 ```bash
-python -m lerobot.scripts.train \
+lerobot-train \
    --config_path=outputs/train/act_aloha_transfer/checkpoints/last/pretrained_model/ \
    --output_dir=outputs/train/act_aloha_transfer_2
    --policy.n_action_steps=80
@@ -148,7 +148,7 @@ python -m lerobot.scripts.train \
 `--config_path` can also accept the repo_id of a repo on the hub that contains a `train_config.json` file, e.g. running:

 ```bash
-python -m lerobot.scripts.train --config_path=lerobot/diffusion_pusht
+lerobot-train --config_path=lerobot/diffusion_pusht
 ```

 will start a training run with the same configuration used for training [lerobot/diffusion_pusht](https://huggingface.co/lerobot/diffusion_pusht)
@@ -160,7 +160,7 @@ Being able to resume a training run is important in case it crashed or aborted f
 Let's reuse the command from the previous run and add a few more options:

 ```bash
-python -m lerobot.scripts.train \
+lerobot-train \
    --policy.type=act \
    --dataset.repo_id=lerobot/aloha_sim_transfer_cube_human \
    --env.type=aloha \
@@ -179,7 +179,7 @@ INFO 2025-01-24 16:10:56 ts/train.py:263 Checkpoint policy after step 100
 Now let's simulate a crash by killing the process (hit `ctrl`+`c`). We can then simply resume this run from the last checkpoint available with:

 ```bash
-python -m lerobot.scripts.train \
+lerobot-train \
    --config_path=outputs/train/run_resumption/checkpoints/last/pretrained_model/ \
    --resume=true
 ```
@@ -190,7 +190,7 @@ Another reason for which you might want to resume a run is simply to extend trai
 You could double the number of steps of the previous run with:

 ```bash
-python -m lerobot.scripts.train \
+lerobot-train \
    --config_path=outputs/train/run_resumption/checkpoints/last/pretrained_model/ \
    --resume=true \
    --steps=200000
@@ -224,7 +224,7 @@ In addition to the features currently in Draccus, we've added a special `.path`
 For example, we could fine-tune a [policy pre-trained on the aloha transfer task](https://huggingface.co/lerobot/act_aloha_sim_transfer_cube_human) on the aloha insertion task. We can achieve this with:

 ```bash
-python -m lerobot.scripts.train \
+lerobot-train \
    --policy.path=lerobot/act_aloha_sim_transfer_cube_human \
    --dataset.repo_id=lerobot/aloha_sim_insertion_human \
    --env.type=aloha \
@@ -270,7 +270,7 @@ We'll summarize here the main use cases to remember from this tutorial.
 #### Train a policy from scratch – CLI

 ```bash
-python -m lerobot.scripts.train \
+lerobot-train \
    --policy.type=act \  # <- select 'act' policy
    --env.type=pusht \  # <- select 'pusht' environment
    --dataset.repo_id=lerobot/pusht  # <- train on this dataset
@@ -279,7 +279,7 @@ python -m lerobot.scripts.train \
 #### Train a policy from scratch - config file + CLI

 ```bash
-python -m lerobot.scripts.train \
+lerobot-train \
    --config_path=path/to/pretrained_model \  # <- can also be a repo_id
    --policy.n_action_steps=80  # <- you may still override values
 ```
@@ -287,7 +287,7 @@ python -m lerobot.scripts.train \
 #### Resume/continue a training run

 ```bash
-python -m lerobot.scripts.train \
+lerobot-train \
    --config_path=checkpoint/pretrained_model/ \
    --resume=true \
    --steps=200000  # <- you can change some training parameters
@@ -296,7 +296,7 @@ python -m lerobot.scripts.train \
 #### Fine-tuning

 ```bash
-python -m lerobot.scripts.train \
+lerobot-train \
    --policy.path=lerobot/act_aloha_sim_transfer_cube_human \  # <- can also be a local path to a checkpoint
    --dataset.repo_id=lerobot/aloha_sim_insertion_human \
    --env.type=aloha \
@@ -0,0 +1,47 @@
+# ------------------------------------------------------------
+
+# config_follower_right = ViperXConfig(
+#     port="/dev/tty.usbserial-FT891KBG",
+#     id="viperx_right",
+# )
+
+# follower_right = ViperX(config_follower_right)
+# follower_right.connect(calibrate=False)
+# follower_right.calibrate()
+# follower_right.disconnect()
+
+# ------------------------------------------------------------
+
+# config_leader_right = WidowXConfig(
+#     port="/dev/tty.usbserial-FT89FM77",
+#     id="widowx_right",
+# )
+
+# leader_right = WidowX(config_leader_right)
+# leader_right.connect(calibrate=False)
+# leader_right.calibrate()
+# leader_right.disconnect()
+
+# ------------------------------------------------------------
+
+# config_follower_left = ViperXConfig(
+#     port="/dev/tty.usbserial-FT89FM09",
+#     id="viperx_left",
+# )
+
+# follower_left = ViperX(config_follower_left)
+# follower_left.connect(calibrate=False)
+# follower_left.calibrate()
+# follower_left.disconnect()
+
+# ------------------------------------------------------------
+
+# config_leader_left = WidowXConfig(
+#     port="/dev/tty.usbserial-FT891KPN",
+#     id="widowx_left",
+# )
+
+# leader_left = WidowX(config_leader_left)
+# leader_left.connect(calibrate=False)
+# leader_left.calibrate()
+# leader_left.disconnect()
@@ -0,0 +1,172 @@
+"""
+ALOHA Bimanual Recording Script
+
+This script records episodes using ALOHA dual-arm system (ViperX followers + WidowX leaders).
+
+Usage:
+1. New dataset: Set RESUME = False
+2. Resume/append: Set RESUME = True (will continue from existing episodes)
+
+The script will:
+- Record NUM_EPISODES new episodes
+- Show progress with total episode count
+- Push dataset to HuggingFace Hub when complete
+"""
+
+from lerobot.cameras.opencv.configuration_opencv import OpenCVCameraConfig
+from lerobot.datasets.lerobot_dataset import LeRobotDataset
+from lerobot.datasets.utils import hw_to_dataset_features
+from lerobot.record import record_loop
+from lerobot.robots.aloha import Aloha, AlohaConfig
+from lerobot.teleoperators.aloha_teleop import AlohaTeleop, AlohaTeleopConfig
+from lerobot.utils.control_utils import (
+    init_keyboard_listener,
+    sanity_check_dataset_name,
+    sanity_check_dataset_robot_compatibility,
+)
+from lerobot.utils.utils import log_say
+from lerobot.utils.visualization_utils import _init_rerun
+
+# Recording configuration
+NUM_EPISODES = 0
+FPS = 30
+EPISODE_TIME_SEC = 200
+RESET_TIME_SEC = 30
+TASK_DESCRIPTION = "First put the Hugging Face t shirt with both arms in the box, then place the hat with the right arm in the box."
+REPO_ID = "pepijn223/aloha_box_2"
+RESUME = True  # Set to True to resume/append to existing dataset
+
+# Create camera configuration
+camera_config = {
+    "front": OpenCVCameraConfig(index_or_path=0, width=640, height=480, fps=FPS),
+    "wrist_right": OpenCVCameraConfig(index_or_path=1, width=640, height=480, fps=FPS),
+    "wrist_left": OpenCVCameraConfig(index_or_path=2, width=640, height=480, fps=FPS),
+}
+
+# ALOHA Robot Configuration (dual ViperX followers)
+aloha_robot_config = AlohaConfig(
+    id="aloha",
+    left_arm_port="/dev/tty.usbserial-FT89FM09",
+    right_arm_port="/dev/tty.usbserial-FT891KBG",
+    left_arm_max_relative_target=20.0,
+    right_arm_max_relative_target=20.0,
+    left_arm_use_degrees=True,
+    right_arm_use_degrees=True,
+    cameras=camera_config,
+)
+
+# ALOHA Teleoperator Configuration (dual WidowX leaders)
+aloha_teleop_config = AlohaTeleopConfig(
+    id="aloha_teleop",
+    left_arm_port="/dev/tty.usbserial-FT891KPN",
+    right_arm_port="/dev/tty.usbserial-FT89FM77",
+    left_arm_gripper_motor="xl430-w250",
+    right_arm_gripper_motor="xc430-w150",
+    left_arm_use_degrees=True,
+    right_arm_use_degrees=True,
+)
+
+# Initialize the robot and teleoperator
+robot = Aloha(aloha_robot_config)
+teleop = AlohaTeleop(aloha_teleop_config)
+
+# Configure the dataset features
+action_features = hw_to_dataset_features(robot.action_features, "action")
+obs_features = hw_to_dataset_features(robot.observation_features, "observation")
+dataset_features = {**action_features, **obs_features}
+
+# Create or resume the dataset
+if RESUME:
+    print(f"Resuming existing dataset: {REPO_ID}")
+    dataset = LeRobotDataset(
+        repo_id=REPO_ID,
+        root=None,  # Use default root
+    )
+
+    # Start image writer for cameras
+    if hasattr(robot, "cameras") and len(robot.cameras) > 0:
+        dataset.start_image_writer(
+            num_processes=0,  # Use threads only
+            num_threads=4 * len(robot.cameras),  # 4 threads per camera
+        )
+
+    # Sanity check compatibility
+    sanity_check_dataset_robot_compatibility(dataset, robot, FPS, dataset_features)
+    print(f"Resumed dataset with {dataset.num_episodes} existing episodes")
+else:
+    print(f"Creating new dataset: {REPO_ID}")
+    # Sanity check dataset name
+    sanity_check_dataset_name(REPO_ID, None)
+
+    # Create new dataset
+    dataset = LeRobotDataset.create(
+        repo_id=REPO_ID,
+        fps=FPS,
+        features=dataset_features,
+        robot_type=robot.name,
+        use_videos=True,
+        image_writer_threads=4 * len(robot.cameras),  # 4 threads per camera
+    )
+
+# Initialize the keyboard listener and rerun visualization
+_, events = init_keyboard_listener()
+_init_rerun(session_name="aloha_recording")
+
+# Connect the robot and teleoperator
+robot.connect()
+teleop.connect()
+
+episode_idx = 0
+total_episodes_to_record = NUM_EPISODES
+existing_episodes = dataset.num_episodes if RESUME else 0
+
+while episode_idx < NUM_EPISODES and not events["stop_recording"]:
+    current_episode = existing_episodes + episode_idx + 1
+    log_say(f"Recording episode {current_episode} (batch: {episode_idx + 1}/{NUM_EPISODES})")
+
+    record_loop(
+        robot=robot,
+        events=events,
+        fps=FPS,
+        teleop=teleop,
+        dataset=dataset,
+        control_time_s=EPISODE_TIME_SEC,
+        single_task=TASK_DESCRIPTION,
+        display_data=True,
+    )
+
+    # Reset the environment if not stopping or re-recording
+    if not events["stop_recording"] and (episode_idx < NUM_EPISODES - 1 or events["rerecord_episode"]):
+        log_say("Reset the environment")
+        record_loop(
+            robot=robot,
+            events=events,
+            fps=FPS,
+            teleop=teleop,
+            control_time_s=RESET_TIME_SEC,
+            single_task=TASK_DESCRIPTION,
+            display_data=True,
+        )
+
+    if events["rerecord_episode"]:
+        log_say("Re-recording episode")
+        events["rerecord_episode"] = False
+        events["exit_early"] = False
+        dataset.clear_episode_buffer()
+        continue
+
+    dataset.save_episode()
+    episode_idx += 1
+
+# Clean up
+log_say("Stop recording")
+robot.disconnect()
+teleop.disconnect()
+
+# Summary
+final_episodes = dataset.num_episodes
+log_say(f"Dataset now contains {final_episodes} episodes total")
+
+# Push to hub
+dataset.push_to_hub()
+log_say(f"Dataset '{REPO_ID}' pushed to HuggingFace Hub")
@@ -0,0 +1,93 @@
+import time
+
+from lerobot.cameras.opencv.configuration_opencv import OpenCVCameraConfig
+from lerobot.robots.viperx import ViperX, ViperXConfig
+from lerobot.teleoperators.widowx import WidowX, WidowXConfig
+from lerobot.utils.visualization_utils import _init_rerun, log_rerun_data
+
+camera_config = {
+    "front": OpenCVCameraConfig(index_or_path=0, width=640, height=480, fps=30),
+    "wrist_right": OpenCVCameraConfig(index_or_path=1, width=640, height=480, fps=30),
+    "wrist_left": OpenCVCameraConfig(index_or_path=2, width=640, height=480, fps=30),
+}
+
+config_follower_right = ViperXConfig(
+    port="/dev/tty.usbserial-FT891KBG",
+    id="viperx_right",
+    max_relative_target=10.0,  # increased from default 5.0 to 10.0
+    use_degrees=True,
+    cameras=camera_config,
+)
+
+config_leader_right = WidowXConfig(
+    port="/dev/tty.usbserial-FT89FM77",
+    id="widowx_right",
+    gripper_motor="xc430-w150",
+    use_degrees=True,
+)
+
+config_follower_left = ViperXConfig(
+    port="/dev/tty.usbserial-FT89FM09",
+    id="viperx_left",
+    max_relative_target=10.0,  # increased from default 5.0 to 10.0
+    use_degrees=True,
+)
+
+config_leader_left = WidowXConfig(
+    port="/dev/tty.usbserial-FT891KPN",
+    id="widowx_left",
+    gripper_motor="xl430-w250",
+    use_degrees=True,
+)
+
+_init_rerun(session_name="teleop")
+
+follower_right = ViperX(config_follower_right)
+follower_right.connect()
+
+leader_right = WidowX(config_leader_right)
+leader_right.connect()
+
+follower_left = ViperX(config_follower_left)
+follower_left.connect()
+
+leader_left = WidowX(config_leader_left)
+leader_left.connect()
+
+
+while True:
+    act_right = leader_right.get_action()
+    obs_right = follower_right.get_observation()
+
+    act_left = leader_left.get_action()
+    obs_left = follower_left.get_observation()
+
+    print("=" * 60)
+    print("ACTION (Leader Right):")
+    for key, value in act_right.items():
+        if key.endswith(".pos"):
+            print(f"  {key:20}: {value:8.3f}")
+
+    print("\nOBSERVATION (Follower Right):")
+    for key, value in obs_right.items():
+        if key.endswith(".pos"):
+            print(f"  {key:20}: {value:8.3f}")
+
+    print("=" * 60)
+    print("ACTION (Leader Left):")
+    for key, value in act_left.items():
+        if key.endswith(".pos"):
+            print(f"  {key:20}: {value:8.3f}")
+
+    print("\nOBSERVATION (Follower Left):")
+    for key, value in obs_left.items():
+        if key.endswith(".pos"):
+            print(f"  {key:20}: {value:8.3f}")
+    print("=" * 60)
+
+    log_rerun_data({**obs_right, **obs_left}, {**act_right, **act_left})
+
+    follower_right.send_action(act_right)
+    follower_left.send_action(act_left)
+
+    time.sleep(0.02)
@@ -18,7 +18,7 @@ Replays the actions of an episode from a dataset on a robot.
 Example:

 ```shell
-python -m lerobot.replay \
+lerobot-replay \
    --robot.type=so100_follower \
    --robot.port=/dev/tty.usbmodem58760431541 \
    --robot.id=black \
@@ -106,6 +106,7 @@ dynamixel = ["dynamixel-sdk>=3.7.31"]
 gamepad = ["lerobot[pygame-dep]", "hidapi>=0.14.0"]
 hopejr = ["lerobot[feetech]", "lerobot[pygame-dep]"]
 lekiwi = ["lerobot[feetech]", "pyzmq>=26.2.1"]
+reachy2 = ["reachy2_sdk>=1.0.14"]
 kinematics = ["lerobot[placo-dep]"]
 intelrealsense = [
    "pyrealsense2>=2.55.1.6486 ; sys_platform != 'darwin'",
@@ -141,6 +142,7 @@ all = [
    "lerobot[gamepad]",
    "lerobot[hopejr]",
    "lerobot[lekiwi]",
+    "lerobot[reachy2]",
    "lerobot[kinematics]",
    "lerobot[intelrealsense]",
    "lerobot[pi0]",
@@ -18,7 +18,7 @@ Helper to recalibrate your device (robot or teleoperator).
 Example:

 ```shell
-python -m lerobot.calibrate \
+lerobot-calibrate \
    --teleop.type=so100_leader \
    --teleop.port=/dev/tty.usbmodem58760431551 \
    --teleop.id=blue
@@ -60,7 +60,7 @@ class OpenCVCamera(Camera):
    or port changes, especially on Linux. Use the provided utility script to find
    available camera indices or paths:
    ```bash
-    python -m lerobot.find_cameras opencv
+    lerobot-find-cameras opencv
    ```

    The camera's default settings (FPS, resolution, color mode) are used unless
@@ -165,8 +165,7 @@ class OpenCVCamera(Camera):
            self.videocapture.release()
            self.videocapture = None
            raise ConnectionError(
-                f"Failed to open {self}."
-                f"Run `python -m lerobot.find_cameras opencv` to find available cameras."
+                f"Failed to open {self}.Run `lerobot-find-cameras opencv` to find available cameras."
            )

        self._configure_capture_settings()
@@ -0,0 +1,16 @@
+# Copyright 2024 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 .configuration_reachy2_camera import Reachy2CameraConfig
+from .reachy2_camera import Reachy2Camera
@@ -0,0 +1,78 @@
+# Copyright 2024 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 dataclasses import dataclass
+
+from ..configs import CameraConfig, ColorMode
+
+
+@CameraConfig.register_subclass("reachy2_camera")
+@dataclass
+class Reachy2CameraConfig(CameraConfig):
+    """Configuration class for Reachy 2 camera devices.
+
+    This class provides configuration options for Reachy 2 cameras,
+    supporting both the teleop and depth cameras. It includes settings
+    for resolution, frame rate, color mode, and the selection of the cameras.
+
+    Example configurations:
+    ```python
+    # Basic configurations
+    Reachy2CameraConfig(
+        name="teleop",
+        image_type="left",
+        ip_address="192.168.0.200",  # IP address of the robot
+        fps=15,
+        width=640,
+        height=480,
+        color_mode=ColorMode.RGB,
+    )  # Left teleop camera, 640x480 @ 15FPS
+    ```
+
+    Attributes:
+        name: Name of the camera device. Can be "teleop" or "depth".
+        image_type: Type of image stream. For "teleop" camera, can be "left" or "right".
+                    For "depth" camera, can be "rgb" or "depth". (depth is not supported yet)
+        fps: Requested frames per second for the color stream.
+        width: Requested frame width in pixels for the color stream.
+        height: Requested frame height in pixels for the color stream.
+        color_mode: Color mode for image output (RGB or BGR). Defaults to RGB.
+        ip_address: IP address of the robot. Defaults to "localhost".
+        port: Port number for the camera server. Defaults to 50065.
+
+    Note:
+        - Only 3-channel color output (RGB/BGR) is currently supported.
+    """
+
+    name: str
+    image_type: str
+    color_mode: ColorMode = ColorMode.RGB
+    ip_address: str | None = "localhost"
+    port: int = 50065
+    # use_depth: bool = False
+
+    def __post_init__(self):
+        if self.name not in ["teleop", "depth"]:
+            raise ValueError(f"`name` is expected to be 'teleop' or 'depth', but {self.name} is provided.")
+        if (self.name == "teleop" and self.image_type not in ["left", "right"]) or (
+            self.name == "depth" and self.image_type not in ["rgb", "depth"]
+        ):
+            raise ValueError(
+                f"`image_type` is expected to be 'left' or 'right' for teleop camera, and 'rgb' or 'depth' for depth camera, but {self.image_type} is provided."
+            )
+
+        if self.color_mode not in ["rgb", "bgr"]:
+            raise ValueError(
+                f"`color_mode` is expected to be 'rgb' or 'bgr', but {self.color_mode} is provided."
+            )
@@ -0,0 +1,288 @@
+# Copyright 2024 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.
+
+"""
+Provides the Reachy2Camera class for capturing frames from Reachy 2 cameras using Reachy 2's CameraManager.
+"""
+
+import logging
+import os
+import platform
+import time
+from threading import Event, Lock, Thread
+from typing import Any
+
+# Fix MSMF hardware transform compatibility for Windows before importing cv2
+if platform.system() == "Windows" and "OPENCV_VIDEOIO_MSMF_ENABLE_HW_TRANSFORMS" not in os.environ:
+    os.environ["OPENCV_VIDEOIO_MSMF_ENABLE_HW_TRANSFORMS"] = "0"
+import cv2
+import numpy as np
+from reachy2_sdk.media.camera import CameraView
+from reachy2_sdk.media.camera_manager import CameraManager
+
+from lerobot.errors import DeviceNotConnectedError
+
+from ..camera import Camera
+from .configuration_reachy2_camera import ColorMode, Reachy2CameraConfig
+
+logger = logging.getLogger(__name__)
+
+
+class Reachy2Camera(Camera):
+    """
+    Manages Reachy 2 camera using Reachy 2 CameraManager.
+
+    This class provides a high-level interface to connect to, configure, and read
+    frames from Reachy 2 cameras. It supports both synchronous and asynchronous
+    frame reading.
+
+    An Reachy2Camera instance requires a camera name (e.g., "teleop") and an image
+    type (e.g., "left") to be specified in the configuration.
+
+    The camera's default settings (FPS, resolution, color mode) are used unless
+    overridden in the configuration.
+    """
+
+    def __init__(self, config: Reachy2CameraConfig):
+        """
+        Initializes the Reachy2Camera instance.
+
+        Args:
+            config: The configuration settings for the camera.
+        """
+        super().__init__(config)
+
+        self.config = config
+
+        self.fps = config.fps
+        self.color_mode = config.color_mode
+
+        self.cam_manager: CameraManager | None = None
+
+        self.thread: Thread | None = None
+        self.stop_event: Event | None = None
+        self.frame_lock: Lock = Lock()
+        self.latest_frame: np.ndarray | None = None
+        self.new_frame_event: Event = Event()
+
+    def __str__(self) -> str:
+        return f"{self.__class__.__name__}({self.config.name}, {self.config.image_type})"
+
+    @property
+    def is_connected(self) -> bool:
+        """Checks if the camera is currently connected and opened."""
+        if self.config.name == "teleop":
+            return self.cam_manager._grpc_connected and self.cam_manager.teleop if self.cam_manager else False
+        elif self.config.name == "depth":
+            return self.cam_manager._grpc_connected and self.cam_manager.depth if self.cam_manager else False
+        else:
+            raise ValueError(f"Invalid camera name '{self.config.name}'. Expected 'teleop' or 'depth'.")
+
+    def connect(self, warmup: bool = True):
+        """
+        Connects to the Reachy2 CameraManager as specified in the configuration.
+        """
+        self.cam_manager = CameraManager(host=self.config.ip_address, port=self.config.port)
+        self.cam_manager.initialize_cameras()
+
+        logger.info(f"{self} connected.")
+
+    @staticmethod
+    def find_cameras(ip_address: str = "localhost", port: int = 50065) -> list[dict[str, Any]]:
+        """
+        Detects available Reachy 2 cameras.
+
+        Returns:
+            List[Dict[str, Any]]: A list of dictionaries,
+            where each dictionary contains 'name', 'stereo',
+            and the default profile properties (width, height, fps).
+        """
+        initialized_cameras = []
+        camera_manager = CameraManager(host=ip_address, port=port)
+
+        for camera in [camera_manager.teleop, camera_manager.depth]:
+            if camera is None:
+                continue
+
+            height, width, _, _, _, _, _ = camera.get_parameters()
+
+            camera_info = {
+                "name": camera._cam_info.name,
+                "stereo": camera._cam_info.stereo,
+                "default_profile": {
+                    "width": width,
+                    "height": height,
+                    "fps": 30,
+                },
+            }
+            initialized_cameras.append(camera_info)
+
+        camera_manager.disconnect()
+        return initialized_cameras
+
+    def read(self, color_mode: ColorMode | None = None) -> np.ndarray:
+        """
+        Reads a single frame synchronously from the camera.
+
+        This is a blocking call.
+
+        Args:
+            color_mode (Optional[ColorMode]): If specified, overrides the default
+                color mode (`self.color_mode`) for this read operation (e.g.,
+                request RGB even if default is BGR).
+
+        Returns:
+            np.ndarray: The captured frame as a NumPy array in the format
+                       (height, width, channels), using the specified or default
+                       color mode and applying any configured rotation.
+        """
+        if not self.is_connected:
+            raise DeviceNotConnectedError(f"{self} is not connected.")
+
+        start_time = time.perf_counter()
+
+        frame = None
+
+        if self.cam_manager is None:
+            raise DeviceNotConnectedError(f"{self} is not connected.")
+        else:
+            if self.config.name == "teleop" and hasattr(self.cam_manager, "teleop"):
+                if self.config.image_type == "left":
+                    frame = self.cam_manager.teleop.get_frame(CameraView.LEFT, size=(640, 480))[0]
+                elif self.config.image_type == "right":
+                    frame = self.cam_manager.teleop.get_frame(CameraView.RIGHT, size=(640, 480))[0]
+            elif self.config.name == "depth" and hasattr(self.cam_manager, "depth"):
+                if self.config.image_type == "depth":
+                    frame = self.cam_manager.depth.get_depth_frame()[0]
+                elif self.config.image_type == "rgb":
+                    frame = self.cam_manager.depth.get_frame(size=(640, 480))[0]
+
+            if frame is None:
+                return np.empty((0, 0, 3), dtype=np.uint8)
+
+            if self.config.color_mode == "rgb":
+                frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
+
+        read_duration_ms = (time.perf_counter() - start_time) * 1e3
+        logger.debug(f"{self} read took: {read_duration_ms:.1f}ms")
+
+        return frame
+
+    def _read_loop(self):
+        """
+        Internal loop run by the background thread for asynchronous reading.
+
+        On each iteration:
+        1. Reads a color frame
+        2. Stores result in latest_frame (thread-safe)
+        3. Sets new_frame_event to notify listeners
+
+        Stops on DeviceNotConnectedError, logs other errors and continues.
+        """
+        while not self.stop_event.is_set():
+            try:
+                color_image = self.read()
+
+                with self.frame_lock:
+                    self.latest_frame = color_image
+                self.new_frame_event.set()
+
+            except DeviceNotConnectedError:
+                break
+            except Exception as e:
+                logger.warning(f"Error reading frame in background thread for {self}: {e}")
+
+    def _start_read_thread(self) -> None:
+        """Starts or restarts the background read thread if it's not running."""
+        if self.thread is not None and self.thread.is_alive():
+            self.thread.join(timeout=0.1)
+        if self.stop_event is not None:
+            self.stop_event.set()
+
+        self.stop_event = Event()
+        self.thread = Thread(target=self._read_loop, args=(), name=f"{self}_read_loop")
+        self.thread.daemon = True
+        self.thread.start()
+
+    def _stop_read_thread(self) -> None:
+        """Signals the background read thread to stop and waits for it to join."""
+        if self.stop_event is not None:
+            self.stop_event.set()
+
+        if self.thread is not None and self.thread.is_alive():
+            self.thread.join(timeout=2.0)
+
+        self.thread = None
+        self.stop_event = None
+
+    def async_read(self, timeout_ms: float = 200) -> np.ndarray:
+        """
+        Reads the latest available frame asynchronously.
+
+        This method retrieves the most recent frame captured by the background
+        read thread. It does not block waiting for the camera hardware directly,
+        but may wait up to timeout_ms for the background thread to provide a frame.
+
+        Args:
+            timeout_ms (float): Maximum time in milliseconds to wait for a frame
+                to become available. Defaults to 200ms (0.2 seconds).
+
+        Returns:
+            np.ndarray: The latest captured frame as a NumPy array in the format
+                       (height, width, channels), processed according to configuration.
+
+        Raises:
+            DeviceNotConnectedError: If the camera is not connected.
+            TimeoutError: If no frame becomes available within the specified timeout.
+            RuntimeError: If an unexpected error occurs.
+        """
+        if not self.is_connected:
+            raise DeviceNotConnectedError(f"{self} is not connected.")
+
+        if self.thread is None or not self.thread.is_alive():
+            self._start_read_thread()
+
+        if not self.new_frame_event.wait(timeout=timeout_ms / 1000.0):
+            thread_alive = self.thread is not None and self.thread.is_alive()
+            raise TimeoutError(
+                f"Timed out waiting for frame from camera {self} after {timeout_ms} ms. "
+                f"Read thread alive: {thread_alive}."
+            )
+
+        with self.frame_lock:
+            frame = self.latest_frame
+            self.new_frame_event.clear()
+
+        if frame is None:
+            raise RuntimeError(f"Internal error: Event set but no frame available for {self}.")
+
+        return frame
+
+    def disconnect(self):
+        """
+        Stops the background read thread (if running).
+
+        Raises:
+            DeviceNotConnectedError: If the camera is already disconnected.
+        """
+        if not self.is_connected and self.thread is None:
+            raise DeviceNotConnectedError(f"{self} not connected.")
+
+        if self.thread is not None:
+            self._stop_read_thread()
+
+        if self.cam_manager is not None:
+            self.cam_manager.disconnect()
+
+        logger.info(f"{self} disconnected.")
@@ -51,7 +51,7 @@ class RealSenseCamera(Camera):

    Use the provided utility script to find available camera indices and default profiles:
    ```bash
-    python -m lerobot.find_cameras realsense
+    lerobot-find-cameras realsense
    ```

    A `RealSenseCamera` instance requires a configuration object specifying the
@@ -176,8 +176,7 @@ class RealSenseCamera(Camera):
            self.rs_profile = None
            self.rs_pipeline = None
            raise ConnectionError(
-                f"Failed to open {self}."
-                "Run `python -m lerobot.find_cameras realsense` to find available cameras."
+                f"Failed to open {self}.Run `lerobot-find-cameras realsense` to find available cameras."
            ) from e

        self._configure_capture_settings()
@@ -37,8 +37,14 @@ def make_cameras_from_configs(camera_configs: dict[str, CameraConfig]) -> dict[s
            from .realsense.camera_realsense import RealSenseCamera

            cameras[key] = RealSenseCamera(cfg)
+
+        elif cfg.type == "reachy2_camera":
+            from .reachy2_camera.reachy2_camera import Reachy2Camera
+
+            cameras[key] = Reachy2Camera(cfg)
+
        else:
-            raise ValueError(f"The motor type '{cfg.type}' is not valid.")
+            raise ValueError(f"The camera type '{cfg.type}' is not valid.")

    return cameras

@@ -825,6 +825,8 @@ class LeRobotDataset(torch.utils.data.Dataset):
        """
        if not episode_data:
            episode_buffer = self.episode_buffer
+        else:
+            episode_buffer = episode_data

        validate_episode_buffer(episode_buffer, self.meta.total_episodes, self.features)

@@ -20,7 +20,7 @@ Helper to find the camera devices available in your system.
 Example:

 ```shell
-python -m lerobot.find_cameras
+lerobot-find-cameras
 ```
 """

@@ -18,7 +18,7 @@ Helper to find the USB port associated with your MotorsBus.
 Example:

 ```shell
-python -m lerobot.find_port
+lerobot-find-port
 ```
 """

@@ -107,6 +107,8 @@ X_SERIES_ENCODINGS_TABLE = {
    "Goal_PWM": X_SERIES_CONTROL_TABLE["Goal_PWM"][1],
    "Goal_Current": X_SERIES_CONTROL_TABLE["Goal_Current"][1],
    "Goal_Velocity": X_SERIES_CONTROL_TABLE["Goal_Velocity"][1],
+    "Goal_Position": X_SERIES_CONTROL_TABLE["Goal_Position"][1],
+    "Present_Position": X_SERIES_CONTROL_TABLE["Present_Position"][1],
    "Present_PWM": X_SERIES_CONTROL_TABLE["Present_PWM"][1],
    "Present_Current": X_SERIES_CONTROL_TABLE["Present_Current"][1],
    "Present_Velocity": X_SERIES_CONTROL_TABLE["Present_Velocity"][1],
@@ -222,7 +222,7 @@ class MotorsBus(abc.ABC):
    A MotorsBus subclass instance requires a port (e.g. `FeetechMotorsBus(port="/dev/tty.usbmodem575E0031751"`)).
    To find the port, you can run our utility script:
    ```bash
-    python -m lerobot.find_port.py
+    lerobot-find-port.py
    >>> Finding all available ports for the MotorsBus.
    >>> ["/dev/tty.usbmodem575E0032081", "/dev/tty.usbmodem575E0031751"]
    >>> Remove the usb cable from your MotorsBus and press Enter when done.
@@ -446,7 +446,7 @@ class MotorsBus(abc.ABC):
        except (FileNotFoundError, OSError, serial.SerialException) as e:
            raise ConnectionError(
                f"\nCould not connect on port '{self.port}'. Make sure you are using the correct port."
-                "\nTry running `python -m lerobot.find_port`\n"
+                "\nTry running `lerobot-find-port`\n"
            ) from e

    @abc.abstractmethod
@@ -30,7 +30,7 @@ pip install -e ".[pi0]"

 Example of finetuning the pi0 pretrained model (`pi0_base` in `openpi`):
 ```bash
-python -m lerobot.scripts.train \
+lerobot-train \
 --policy.path=lerobot/pi0 \
 --dataset.repo_id=danaaubakirova/koch_test
 ```
@@ -38,7 +38,7 @@ python -m lerobot.scripts.train \
 Example of finetuning the pi0 neural network with PaliGemma and expert Gemma
 pretrained with VLM default parameters before pi0 finetuning:
 ```bash
-python -m lerobot.scripts.train \
+lerobot-train \
 --policy.type=pi0 \
 --dataset.repo_id=danaaubakirova/koch_test
 ```
@@ -25,14 +25,14 @@ Disclaimer: It is not expected to perform as well as the original implementation

 Example of finetuning the pi0+FAST pretrained model (`pi0_fast_base` in `openpi`):
 ```bash
-python -m lerobot.scripts.train \
+lerobot-train \
 --policy.path=lerobot/pi0fast_base \
 --dataset.repo_id=danaaubakirova/koch_test
 ```

 Example of training the pi0+FAST neural network with from scratch:
 ```bash
-python -m lerobot.scripts.train \
+lerobot-train \
 --policy.type=pi0fast \
 --dataset.repo_id=danaaubakirova/koch_test
 ```
@@ -28,7 +28,7 @@ pip install -e ".[smolvla]"

 Example of finetuning the smolvla pretrained model (`smolvla_base`):
 ```bash
-python -m lerobot.scripts.train \
+lerobot-train \
 --policy.path=lerobot/smolvla_base \
 --dataset.repo_id=danaaubakirova/svla_so100_task1_v3 \
 --batch_size=64 \
@@ -38,7 +38,7 @@ python -m lerobot.scripts.train \
 Example of finetuning a smolVLA. SmolVLA is composed of a pretrained VLM,
 and an action expert.
 ```bash
-python -m lerobot.scripts.train \
+lerobot-train \
 --policy.type=smolvla \
 --dataset.repo_id=danaaubakirova/svla_so100_task1_v3 \
 --batch_size=64 \
@@ -18,7 +18,7 @@ Records a dataset. Actions for the robot can be either generated by teleoperatio
 Example:

 ```shell
-python -m lerobot.record \
+lerobot-record \
    --robot.type=so100_follower \
    --robot.port=/dev/tty.usbmodem58760431541 \
    --robot.cameras="{laptop: {type: opencv, camera_index: 0, width: 640, height: 480}}" \
@@ -36,7 +36,7 @@ python -m lerobot.record \

 Example recording with bimanual so100:
 ```shell
-python -m lerobot.record \
+lerobot-record \
  --robot.type=bi_so100_follower \
  --robot.left_arm_port=/dev/tty.usbmodem5A460851411 \
  --robot.right_arm_port=/dev/tty.usbmodem5A460812391 \
@@ -209,7 +209,14 @@ def record_loop(
            (
                t
                for t in teleop
-                if isinstance(t, (so100_leader.SO100Leader, so101_leader.SO101Leader, koch_leader.KochLeader))
+                if isinstance(
+                    t,
+                    (
+                        so100_leader.SO100Leader,
+                        so101_leader.SO101Leader,
+                        koch_leader.KochLeader,
+                    ),
+                )
            ),
            None,
        )
@@ -18,7 +18,7 @@ Replays the actions of an episode from a dataset on a robot.
 Examples:

 ```shell
-python -m lerobot.replay \
+lerobot-replay \
    --robot.type=so100_follower \
    --robot.port=/dev/tty.usbmodem58760431541 \
    --robot.id=black \
@@ -28,7 +28,7 @@ python -m lerobot.replay \

 Example replay with bimanual so100:
 ```shell
-python -m lerobot.replay \
+lerobot-replay \
  --robot.type=bi_so100_follower \
  --robot.left_arm_port=/dev/tty.usbmodem5A460851411 \
  --robot.right_arm_port=/dev/tty.usbmodem5A460812391 \
@@ -55,6 +55,7 @@ from lerobot.robots import (  # noqa: F401
    hope_jr,
    koch_follower,
    make_robot_from_config,
+    reachy2,
    so100_follower,
    so101_follower,
 )
@@ -0,0 +1,4 @@
+from .aloha import Aloha
+from .config_aloha import AlohaConfig
+
+__all__ = ["Aloha", "AlohaConfig"]
@@ -0,0 +1,161 @@
+#!/usr/bin/env python
+
+# Copyright 2024 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.
+
+import logging
+import time
+from functools import cached_property
+from typing import Any
+
+from lerobot.cameras.utils import make_cameras_from_configs
+from lerobot.robots.viperx import ViperX
+from lerobot.robots.viperx.config_viperx import ViperXConfig
+
+from ..robot import Robot
+from .config_aloha import AlohaConfig
+
+logger = logging.getLogger(__name__)
+
+
+class Aloha(Robot):
+    """
+    ALOHA Bimanual Robot System using dual ViperX follower arms.
+    Based on the ALOHA (A Low-cost Open-source Hardware System for Bimanual Teleoperation) design.
+    """
+
+    config_class = AlohaConfig
+    name = "aloha"
+
+    def __init__(self, config: AlohaConfig):
+        super().__init__(config)
+        self.config = config
+
+        left_arm_config = ViperXConfig(
+            id=f"{config.id}_left" if config.id else None,
+            calibration_dir=config.calibration_dir,
+            port=config.left_arm_port,
+            max_relative_target=config.left_arm_max_relative_target,
+            use_degrees=config.left_arm_use_degrees,
+            cameras={},
+        )
+
+        right_arm_config = ViperXConfig(
+            id=f"{config.id}_right" if config.id else None,
+            calibration_dir=config.calibration_dir,
+            port=config.right_arm_port,
+            max_relative_target=config.right_arm_max_relative_target,
+            use_degrees=config.right_arm_use_degrees,
+            cameras={},
+        )
+
+        self.left_arm = ViperX(left_arm_config)
+        self.right_arm = ViperX(right_arm_config)
+        self.cameras = make_cameras_from_configs(config.cameras)
+
+    @property
+    def _motors_ft(self) -> dict[str, type]:
+        return {f"left_{motor}.pos": float for motor in self.left_arm.bus.motors} | {
+            f"right_{motor}.pos": float for motor in self.right_arm.bus.motors
+        }
+
+    @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 self._motors_ft
+
+    @property
+    def is_connected(self) -> bool:
+        return (
+            self.left_arm.bus.is_connected
+            and self.right_arm.bus.is_connected
+            and all(cam.is_connected for cam in self.cameras.values())
+        )
+
+    def connect(self, calibrate: bool = True) -> None:
+        self.left_arm.connect(calibrate)
+        self.right_arm.connect(calibrate)
+
+        for cam in self.cameras.values():
+            cam.connect()
+
+    @property
+    def is_calibrated(self) -> bool:
+        return self.left_arm.is_calibrated and self.right_arm.is_calibrated
+
+    def calibrate(self) -> None:
+        self.left_arm.calibrate()
+        self.right_arm.calibrate()
+
+    def configure(self) -> None:
+        self.left_arm.configure()
+        self.right_arm.configure()
+
+    def setup_motors(self) -> None:
+        self.left_arm.setup_motors()
+        self.right_arm.setup_motors()
+
+    def get_observation(self) -> dict[str, Any]:
+        obs_dict = {}
+
+        # Add "left_" prefix
+        left_obs = self.left_arm.get_observation()
+        obs_dict.update({f"left_{key}": value for key, value in left_obs.items()})
+
+        # Add "right_" prefix
+        right_obs = self.right_arm.get_observation()
+        obs_dict.update({f"right_{key}": value for key, value in right_obs.items()})
+
+        for cam_key, cam in self.cameras.items():
+            start = time.perf_counter()
+            obs_dict[cam_key] = cam.async_read()
+            dt_ms = (time.perf_counter() - start) * 1e3
+            logger.debug(f"{self} read {cam_key}: {dt_ms:.1f}ms")
+
+        return obs_dict
+
+    def send_action(self, action: dict[str, Any]) -> dict[str, Any]:
+        # Remove "left_" prefix
+        left_action = {
+            key.removeprefix("left_"): value for key, value in action.items() if key.startswith("left_")
+        }
+        # Remove "right_" prefix
+        right_action = {
+            key.removeprefix("right_"): value for key, value in action.items() if key.startswith("right_")
+        }
+
+        send_action_left = self.left_arm.send_action(left_action)
+        send_action_right = self.right_arm.send_action(right_action)
+
+        # Add prefixes back
+        prefixed_send_action_left = {f"left_{key}": value for key, value in send_action_left.items()}
+        prefixed_send_action_right = {f"right_{key}": value for key, value in send_action_right.items()}
+
+        return {**prefixed_send_action_left, **prefixed_send_action_right}
+
+    def disconnect(self):
+        self.left_arm.disconnect()
+        self.right_arm.disconnect()
+
+        for cam in self.cameras.values():
+            cam.disconnect()
@@ -0,0 +1,39 @@
+#!/usr/bin/env python
+
+# Copyright 2024 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 dataclasses import dataclass, field
+
+from lerobot.cameras import CameraConfig
+
+from ..config import RobotConfig
+
+
+@RobotConfig.register_subclass("aloha")
+@dataclass
+class AlohaConfig(RobotConfig):
+    left_arm_port: str
+    right_arm_port: str
+
+    # Optional parameters for left arm (ViperX)
+    left_arm_max_relative_target: float | dict[str, float] = 20.0
+    left_arm_use_degrees: bool = True
+
+    # Optional parameters for right arm (ViperX)
+    right_arm_max_relative_target: float | dict[str, float] = 20.0
+    right_arm_use_degrees: bool = True
+
+    # cameras (shared between both arms)
+    cameras: dict[str, CameraConfig] = field(default_factory=dict)
@@ -29,10 +29,10 @@ class BiSO100FollowerConfig(RobotConfig):

    # Optional
    left_arm_disable_torque_on_disconnect: bool = True
-    left_arm_max_relative_target: int | None = None
+    left_arm_max_relative_target: float | dict[str, float] | None = None
    left_arm_use_degrees: bool = False
    right_arm_disable_torque_on_disconnect: bool = True
-    right_arm_max_relative_target: int | None = None
+    right_arm_max_relative_target: float | dict[str, float] | None = None
    right_arm_use_degrees: bool = False

    # cameras (shared between both arms)
@@ -44,8 +44,8 @@ class HopeJrArmConfig(RobotConfig):
    disable_torque_on_disconnect: bool = True

    # `max_relative_target` limits the magnitude of the relative positional target vector for safety purposes.
-    # Set this to a positive scalar to have the same value for all motors, or a list that is the same length as
-    # the number of motors in your follower arms.
-    max_relative_target: int | None = None
+    # Set this to a positive scalar to have the same value for all motors, or a dictionary that maps motor
+    # names to the max_relative_target value for that motor.
+    max_relative_target: float | dict[str, float] | None = None

    cameras: dict[str, CameraConfig] = field(default_factory=dict)
@@ -28,9 +28,9 @@ class KochFollowerConfig(RobotConfig):
    disable_torque_on_disconnect: bool = True

    # `max_relative_target` limits the magnitude of the relative positional target vector for safety purposes.
-    # Set this to a positive scalar to have the same value for all motors, or a list that is the same length as
-    # the number of motors in your follower arms.
-    max_relative_target: int | None = None
+    # Set this to a positive scalar to have the same value for all motors, or a dictionary that maps motor
+    # names to the max_relative_target value for that motor.
+    max_relative_target: float | dict[str, float] | None = None

    # cameras
    cameras: dict[str, CameraConfig] = field(default_factory=dict)
@@ -110,6 +110,7 @@ class KochFollower(Robot):
        return self.bus.is_calibrated

    def calibrate(self) -> None:
+        self.bus.disable_torque()
        if self.calibration:
            # Calibration file exists, ask user whether to use it or run new calibration
            user_input = input(
@@ -120,7 +121,6 @@ class KochFollower(Robot):
                self.bus.write_calibration(self.calibration)
                return
        logger.info(f"\nRunning calibration of {self}")
-        self.bus.disable_torque()
        for motor in self.bus.motors:
            self.bus.write("Operating_Mode", motor, OperatingMode.EXTENDED_POSITION.value)

@@ -39,9 +39,9 @@ class LeKiwiConfig(RobotConfig):
    disable_torque_on_disconnect: bool = True

    # `max_relative_target` limits the magnitude of the relative positional target vector for safety purposes.
-    # Set this to a positive scalar to have the same value for all motors, or a list that is the same length as
-    # the number of motors in your follower arms.
-    max_relative_target: int | None = None
+    # Set this to a positive scalar to have the same value for all motors, or a dictionary that maps motor
+    # names to the max_relative_target value for that motor.
+    max_relative_target: float | dict[str, float] | None = None

    cameras: dict[str, CameraConfig] = field(default_factory=lekiwi_cameras_config)

@@ -0,0 +1,25 @@
+#!/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 .configuration_reachy2 import Reachy2RobotConfig
+from .robot_reachy2 import (
+    REACHY2_ANTENNAS_JOINTS,
+    REACHY2_L_ARM_JOINTS,
+    REACHY2_NECK_JOINTS,
+    REACHY2_R_ARM_JOINTS,
+    REACHY2_VEL,
+    Reachy2Robot,
+)
@@ -0,0 +1,107 @@
+# Copyright 2024 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 dataclasses import dataclass, field
+
+from lerobot.cameras import CameraConfig
+from lerobot.cameras.configs import ColorMode
+from lerobot.cameras.reachy2_camera import Reachy2CameraConfig
+
+from ..config import RobotConfig
+
+
+@RobotConfig.register_subclass("reachy2")
+@dataclass
+class Reachy2RobotConfig(RobotConfig):
+    # `max_relative_target` limits the magnitude of the relative positional target vector for safety purposes.
+    # Set this to a positive scalar to have the same value for all motors.
+    max_relative_target: float | None = None
+
+    # IP address of the Reachy 2 robot
+    ip_address: str | None = "localhost"
+
+    # If True, turn_off_smoothly() will be sent to the robot before disconnecting.
+    disable_torque_on_disconnect: bool = False
+
+    # Tag for external commands control
+    # Set to True if you use an external commands system to control the robot,
+    # such as the official teleoperation application: https://github.com/pollen-robotics/Reachy2Teleoperation
+    # If True, robot.send_action() will not send commands to the robot.
+    use_external_commands: bool = False
+
+    # Robot parts
+    # Set to False to not add the corresponding joints part to the robot list of joints.
+    # By default, all parts are set to True.
+    with_mobile_base: bool = True
+    with_l_arm: bool = True
+    with_r_arm: bool = True
+    with_neck: bool = True
+    with_antennas: bool = True
+
+    # Robot cameras
+    # Set to True if you want to use the corresponding cameras in the observations.
+    # By default, only the teleop cameras are used.
+    with_left_teleop_camera: bool = True
+    with_right_teleop_camera: bool = True
+    with_torso_camera: bool = False
+
+    cameras: dict[str, CameraConfig] = field(default_factory=dict)
+
+    def __post_init__(self) -> None:
+        # Add cameras with same ip_address as the robot
+        if self.with_left_teleop_camera:
+            self.cameras["teleop_left"] = Reachy2CameraConfig(
+                name="teleop",
+                image_type="left",
+                ip_address=self.ip_address,
+                fps=15,
+                width=640,
+                height=480,
+                color_mode=ColorMode.RGB,
+            )
+        if self.with_right_teleop_camera:
+            self.cameras["teleop_right"] = Reachy2CameraConfig(
+                name="teleop",
+                image_type="right",
+                ip_address=self.ip_address,
+                fps=15,
+                width=640,
+                height=480,
+                color_mode=ColorMode.RGB,
+            )
+        if self.with_torso_camera:
+            self.cameras["torso_rgb"] = Reachy2CameraConfig(
+                name="depth",
+                image_type="rgb",
+                ip_address=self.ip_address,
+                fps=15,
+                width=640,
+                height=480,
+                color_mode=ColorMode.RGB,
+            )
+
+        super().__post_init__()
+
+        if not (
+            self.with_mobile_base
+            or self.with_l_arm
+            or self.with_r_arm
+            or self.with_neck
+            or self.with_antennas
+        ):
+            raise ValueError(
+                "No Reachy2Robot part used.\n"
+                "At least one part of the robot must be set to True "
+                "(with_mobile_base, with_l_arm, with_r_arm, with_neck, with_antennas)"
+            )
@@ -0,0 +1,230 @@
+#!/usr/bin/env python
+
+# Copyright 2024 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.
+
+import time
+from typing import Any
+
+import numpy as np
+from reachy2_sdk import ReachySDK
+
+from lerobot.cameras.utils import make_cameras_from_configs
+
+from ..robot import Robot
+from ..utils import ensure_safe_goal_position
+from .configuration_reachy2 import Reachy2RobotConfig
+
+# {lerobot_keys: reachy2_sdk_keys}
+REACHY2_NECK_JOINTS = {
+    "neck_yaw.pos": "head.neck.yaw",
+    "neck_pitch.pos": "head.neck.pitch",
+    "neck_roll.pos": "head.neck.roll",
+}
+
+REACHY2_ANTENNAS_JOINTS = {
+    "l_antenna.pos": "head.l_antenna",
+    "r_antenna.pos": "head.r_antenna",
+}
+
+REACHY2_R_ARM_JOINTS = {
+    "r_shoulder_pitch.pos": "r_arm.shoulder.pitch",
+    "r_shoulder_roll.pos": "r_arm.shoulder.roll",
+    "r_elbow_yaw.pos": "r_arm.elbow.yaw",
+    "r_elbow_pitch.pos": "r_arm.elbow.pitch",
+    "r_wrist_roll.pos": "r_arm.wrist.roll",
+    "r_wrist_pitch.pos": "r_arm.wrist.pitch",
+    "r_wrist_yaw.pos": "r_arm.wrist.yaw",
+    "r_gripper.pos": "r_arm.gripper",
+}
+
+REACHY2_L_ARM_JOINTS = {
+    "l_shoulder_pitch.pos": "l_arm.shoulder.pitch",
+    "l_shoulder_roll.pos": "l_arm.shoulder.roll",
+    "l_elbow_yaw.pos": "l_arm.elbow.yaw",
+    "l_elbow_pitch.pos": "l_arm.elbow.pitch",
+    "l_wrist_roll.pos": "l_arm.wrist.roll",
+    "l_wrist_pitch.pos": "l_arm.wrist.pitch",
+    "l_wrist_yaw.pos": "l_arm.wrist.yaw",
+    "l_gripper.pos": "l_arm.gripper",
+}
+
+REACHY2_VEL = {
+    "mobile_base.vx": "vx",
+    "mobile_base.vy": "vy",
+    "mobile_base.vtheta": "vtheta",
+}
+
+
+class Reachy2Robot(Robot):
+    """
+    [Reachy 2](https://www.pollen-robotics.com/reachy/), by Pollen Robotics.
+    """
+
+    config_class = Reachy2RobotConfig
+    name = "reachy2"
+
+    def __init__(self, config: Reachy2RobotConfig):
+        super().__init__(config)
+
+        self.config = config
+        self.robot_type = self.config.type
+        self.use_external_commands = self.config.use_external_commands
+
+        self.reachy: None | ReachySDK = None
+        self.cameras = make_cameras_from_configs(config.cameras)
+
+        self.logs: dict[str, float] = {}
+
+        self.joints_dict: dict[str, str] = self._generate_joints_dict()
+
+    @property
+    def observation_features(self) -> dict[str, Any]:
+        return {**self.motors_features, **self.camera_features}
+
+    @property
+    def action_features(self) -> dict[str, type]:
+        return self.motors_features
+
+    @property
+    def camera_features(self) -> dict[str, tuple[int | None, int | None, int]]:
+        return {cam: (self.cameras[cam].height, self.cameras[cam].width, 3) for cam in self.cameras}
+
+    @property
+    def motors_features(self) -> dict[str, type]:
+        if self.config.with_mobile_base:
+            return {
+                **dict.fromkeys(
+                    self.joints_dict.keys(),
+                    float,
+                ),
+                **dict.fromkeys(
+                    REACHY2_VEL.keys(),
+                    float,
+                ),
+            }
+        else:
+            return dict.fromkeys(self.joints_dict.keys(), float)
+
+    @property
+    def is_connected(self) -> bool:
+        return self.reachy.is_connected() if self.reachy is not None else False
+
+    def connect(self, calibrate: bool = False) -> None:
+        self.reachy = ReachySDK(self.config.ip_address)
+        if not self.is_connected:
+            raise ConnectionError()
+
+        for cam in self.cameras.values():
+            cam.connect()
+
+        self.configure()
+
+    def configure(self) -> None:
+        if self.reachy is not None:
+            self.reachy.turn_on()
+            self.reachy.reset_default_limits()
+
+    @property
+    def is_calibrated(self) -> bool:
+        return True
+
+    def calibrate(self) -> None:
+        pass
+
+    def _generate_joints_dict(self) -> dict[str, str]:
+        joints = {}
+        if self.config.with_neck:
+            joints.update(REACHY2_NECK_JOINTS)
+        if self.config.with_l_arm:
+            joints.update(REACHY2_L_ARM_JOINTS)
+        if self.config.with_r_arm:
+            joints.update(REACHY2_R_ARM_JOINTS)
+        if self.config.with_antennas:
+            joints.update(REACHY2_ANTENNAS_JOINTS)
+        return joints
+
+    def _get_state(self) -> dict[str, float]:
+        if self.reachy is not None:
+            pos_dict = {k: self.reachy.joints[v].present_position for k, v in self.joints_dict.items()}
+            if not self.config.with_mobile_base:
+                return pos_dict
+            vel_dict = {k: self.reachy.mobile_base.odometry[v] for k, v in REACHY2_VEL.items()}
+            return {**pos_dict, **vel_dict}
+        else:
+            return {}
+
+    def get_observation(self) -> dict[str, np.ndarray]:
+        obs_dict: dict[str, Any] = {}
+
+        # Read Reachy 2 state
+        before_read_t = time.perf_counter()
+        obs_dict.update(self._get_state())
+        self.logs["read_pos_dt_s"] = time.perf_counter() - before_read_t
+
+        # Capture images from cameras
+        for cam_key, cam in self.cameras.items():
+            obs_dict[cam_key] = cam.async_read()
+
+        return obs_dict
+
+    def send_action(self, action: dict[str, Any]) -> dict[str, Any]:
+        if self.reachy is not None:
+            if not self.is_connected:
+                raise ConnectionError()
+
+            before_write_t = time.perf_counter()
+
+            vel = {}
+            goal_pos = {}
+            for key, val in action.items():
+                if key not in self.joints_dict:
+                    if key not in REACHY2_VEL:
+                        raise KeyError(f"Key '{key}' is not a valid motor key in Reachy 2.")
+                    else:
+                        vel[REACHY2_VEL[key]] = float(val)
+                else:
+                    if not self.use_external_commands and self.config.max_relative_target is not None:
+                        goal_pos[key] = float(val)
+                        goal_present_pos = {
+                            key: (
+                                goal_pos[key],
+                                self.reachy.joints[self.joints_dict[key]].present_position,
+                            )
+                        }
+                        safe_goal_pos = ensure_safe_goal_position(
+                            goal_present_pos, float(self.config.max_relative_target)
+                        )
+                        val = safe_goal_pos[key]
+                    self.reachy.joints[self.joints_dict[key]].goal_position = float(val)
+
+            if self.config.with_mobile_base:
+                self.reachy.mobile_base.set_goal_speed(vel["vx"], vel["vy"], vel["vtheta"])
+
+            # We don't send the goal positions if we control Reachy 2 externally
+            if not self.use_external_commands:
+                self.reachy.send_goal_positions()
+                if self.config.with_mobile_base:
+                    self.reachy.mobile_base.send_speed_command()
+
+            self.logs["write_pos_dt_s"] = time.perf_counter() - before_write_t
+        return action
+
+    def disconnect(self) -> None:
+        if self.reachy is not None:
+            for cam in self.cameras.values():
+                cam.disconnect()
+            if self.config.disable_torque_on_disconnect:
+                self.reachy.turn_off_smoothly()
+            self.reachy.disconnect()
@@ -30,9 +30,9 @@ class SO100FollowerConfig(RobotConfig):
    disable_torque_on_disconnect: bool = True

    # `max_relative_target` limits the magnitude of the relative positional target vector for safety purposes.
-    # Set this to a positive scalar to have the same value for all motors, or a list that is the same length as
-    # the number of motors in your follower arms.
-    max_relative_target: int | None = None
+    # Set this to a positive scalar to have the same value for all motors, or a dictionary that maps motor
+    # names to the max_relative_target value for that motor.
+    max_relative_target: float | dict[str, float] | None = None

    # cameras
    cameras: dict[str, CameraConfig] = field(default_factory=dict)
@@ -161,6 +161,11 @@ class SO100Follower(Robot):
                self.bus.write("I_Coefficient", motor, 0)
                self.bus.write("D_Coefficient", motor, 32)

+                if motor == "gripper":
+                    self.bus.write("Max_Torque_Limit", motor, 500)  # 50% of max torque to avoid burnout
+                    self.bus.write("Protection_Current", motor, 250)  # 50% of max current to avoid burnout
+                    self.bus.write("Overload_Torque", motor, 25)  # 25% torque when overloaded
+
    def setup_motors(self) -> None:
        for motor in reversed(self.bus.motors):
            input(f"Connect the controller board to the '{motor}' motor only and press enter.")
@@ -30,9 +30,9 @@ class SO101FollowerConfig(RobotConfig):
    disable_torque_on_disconnect: bool = True

    # `max_relative_target` limits the magnitude of the relative positional target vector for safety purposes.
-    # Set this to a positive scalar to have the same value for all motors, or a list that is the same length as
-    # the number of motors in your follower arms.
-    max_relative_target: int | None = None
+    # Set this to a positive scalar to have the same value for all motors, or a dictionary that maps motor
+    # names to the max_relative_target value for that motor.
+    max_relative_target: float | dict[str, float] | None = None

    # cameras
    cameras: dict[str, CameraConfig] = field(default_factory=dict)
@@ -157,6 +157,13 @@ class SO101Follower(Robot):
                self.bus.write("I_Coefficient", motor, 0)
                self.bus.write("D_Coefficient", motor, 32)

+                if motor == "gripper":
+                    self.bus.write(
+                        "Max_Torque_Limit", motor, 500
+                    )  # 50% of the max torque limit to avoid burnout
+                    self.bus.write("Protection_Current", motor, 250)  # 50% of max current to avoid burnout
+                    self.bus.write("Overload_Torque", motor, 25)  # 25% torque when overloaded
+
    def setup_motors(self) -> None:
        for motor in reversed(self.bus.motors):
            input(f"Connect the controller board to the '{motor}' motor only and press enter.")
@@ -24,11 +24,6 @@ from ..config import RobotConfig
@RobotConfig.register_subclass("stretch3")
@dataclass
 class Stretch3RobotConfig(RobotConfig):
-    # `max_relative_target` limits the magnitude of the relative positional target vector for safety purposes.
-    # Set this to a positive scalar to have the same value for all motors, or a list that is the same length as
-    # the number of motors in your follower arms.
-    max_relative_target: int | None = None
-
    # cameras
    cameras: dict[str, CameraConfig] = field(
        default_factory=lambda: {
@@ -61,6 +61,10 @@ def make_robot_from_config(config: RobotConfig) -> Robot:
        from .bi_so100_follower import BiSO100Follower

        return BiSO100Follower(config)
+    elif config.type == "reachy2":
+        from .reachy2 import Reachy2Robot
+
+        return Reachy2Robot(config)
    elif config.type == "mock_robot":
        from tests.mocks.mock_robot import MockRobot

@@ -70,7 +74,7 @@ def make_robot_from_config(config: RobotConfig) -> Robot:


 def ensure_safe_goal_position(
-    goal_present_pos: dict[str, tuple[float, float]], max_relative_target: float | dict[float]
+    goal_present_pos: dict[str, tuple[float, float]], max_relative_target: float | dict[str, float]
 ) -> dict[str, float]:
    """Caps relative action target magnitude for safety."""

@@ -141,10 +141,10 @@ python lerobot/scripts/control_robot.py \

 ## Train a policy

-To train a policy to control your robot, use the [`python -m lerobot.scripts.train`](../src/lerobot/scripts/train.py) script. A few arguments are required. Here is an example command:
+To train a policy to control your robot, use the [`lerobot-train`](../src/lerobot/scripts/train.py) script. A few arguments are required. Here is an example command:

 ```bash
-python -m lerobot.scripts.train \
+lerobot-train \
  --dataset.repo_id=${HF_USER}/aloha_test \
  --policy.type=act \
  --output_dir=outputs/train/act_aloha_test \
@@ -28,18 +28,21 @@ class ViperXConfig(RobotConfig):

    # /!\ FOR SAFETY, READ THIS /!\
    # `max_relative_target` limits the magnitude of the relative positional target vector for safety purposes.
-    # Set this to a positive scalar to have the same value for all motors, or a list that is the same length as
-    # the number of motors in your follower arms.
+    # Set this to a positive scalar to have the same value for all motors, or a dictionary that maps motor
+    # names to the max_relative_target value for that motor.
    # For Aloha, for every goal position request, motor rotations are capped at 5 degrees by default.
    # When you feel more confident with teleoperation or running the policy, you can extend
    # this safety limit and even removing it by setting it to `null`.
    # Also, everything is expected to work safely out-of-the-box, but we highly advise to
    # first try to teleoperate the grippers only (by commenting out the rest of the motors in this yaml),
    # then to gradually add more motors (by uncommenting), until you can teleoperate both arms fully
-    max_relative_target: int | None = 5
+    max_relative_target: float | dict[str, float] = 5.0

    # cameras
    cameras: dict[str, CameraConfig] = field(default_factory=dict)
    # Troubleshooting: If one of your IntelRealSense cameras freeze during
    # data recording due to bandwidth limit, you might need to plug the camera
    # on another USB hub or PCIe card.
+
+    # Set to `True` for backward compatibility with previous policies/dataset
+    use_degrees: bool = False
@@ -18,7 +18,6 @@ from functools import cached_property
 from typing import Any

 from lerobot.cameras.utils import make_cameras_from_configs
-from lerobot.constants import OBS_STATE
 from lerobot.errors import DeviceAlreadyConnectedError, DeviceNotConnectedError
 from lerobot.motors import Motor, MotorCalibration, MotorNormMode
 from lerobot.motors.dynamixel import (
@@ -45,22 +44,23 @@ class ViperX(Robot):
        self,
        config: ViperXConfig,
    ):
-        raise NotImplementedError
        super().__init__(config)
        self.config = config
+        norm_mode_body = MotorNormMode.DEGREES if config.use_degrees else MotorNormMode.RANGE_M100_100
        self.bus = DynamixelMotorsBus(
            port=self.config.port,
            motors={
-                "waist": Motor(1, "xm540-w270", MotorNormMode.RANGE_M100_100),
-                "shoulder": Motor(2, "xm540-w270", MotorNormMode.RANGE_M100_100),
-                "shoulder_shadow": Motor(3, "xm540-w270", MotorNormMode.RANGE_M100_100),
-                "elbow": Motor(4, "xm540-w270", MotorNormMode.RANGE_M100_100),
-                "elbow_shadow": Motor(5, "xm540-w270", MotorNormMode.RANGE_M100_100),
-                "forearm_roll": Motor(6, "xm540-w270", MotorNormMode.RANGE_M100_100),
-                "wrist_angle": Motor(7, "xm540-w270", MotorNormMode.RANGE_M100_100),
-                "wrist_rotate": Motor(8, "xm430-w350", MotorNormMode.RANGE_M100_100),
+                "waist": Motor(1, "xm540-w270", norm_mode_body),
+                "shoulder": Motor(2, "xm540-w270", norm_mode_body),
+                "shoulder_shadow": Motor(3, "xm540-w270", norm_mode_body),
+                "elbow": Motor(4, "xm540-w270", norm_mode_body),
+                "elbow_shadow": Motor(5, "xm540-w270", norm_mode_body),
+                "forearm_roll": Motor(6, "xm540-w270", norm_mode_body),
+                "wrist_angle": Motor(7, "xm540-w270", norm_mode_body),
+                "wrist_rotate": Motor(8, "xm430-w350", norm_mode_body),
                "gripper": Motor(9, "xm430-w350", MotorNormMode.RANGE_0_100),
            },
+            calibration=self.calibration,
        )
        self.cameras = make_cameras_from_configs(config.cameras)

@@ -96,6 +96,9 @@ class ViperX(Robot):

        self.bus.connect()
        if not self.is_calibrated and calibrate:
+            logger.info(
+                "Mismatch between calibration values in the motor and the calibration file or no calibration file found"
+            )
            self.calibrate()

        for cam in self.cameras.values():
@@ -109,16 +112,24 @@ class ViperX(Robot):
        return self.bus.is_calibrated

    def calibrate(self) -> None:
-        raise NotImplementedError  # TODO(aliberts): adapt code below (copied from koch
-        logger.info(f"\nRunning calibration of {self}")
        self.bus.disable_torque()
+        if self.calibration:
+            # Calibration file exists, ask user whether to use it or run new calibration
+            user_input = input(
+                f"Press ENTER to use provided calibration file associated with the id {self.id}, or type 'c' and press ENTER to run calibration: "
+            )
+            if user_input.strip().lower() != "c":
+                logger.info(f"Writing calibration file associated with the id {self.id} to the motors")
+                self.bus.write_calibration(self.calibration)
+                return
+        logger.info(f"\nRunning calibration of {self}")
        for motor in self.bus.motors:
            self.bus.write("Operating_Mode", motor, OperatingMode.EXTENDED_POSITION.value)

-        input("Move robot to the middle of its range of motion and press ENTER....")
+        input(f"Move {self} to the middle of its range of motion and press ENTER....")
        homing_offsets = self.bus.set_half_turn_homings()

-        full_turn_motors = ["shoulder_pan", "wrist_roll"]
+        full_turn_motors = ["shoulder", "forearm_roll", "wrist_rotate"]
        unknown_range_motors = [motor for motor in self.bus.motors if motor not in full_turn_motors]
        print(
            f"Move all joints except {full_turn_motors} sequentially through their entire "
@@ -153,33 +164,23 @@ class ViperX(Robot):
            self.bus.write("Secondary_ID", "shoulder_shadow", 2)
            self.bus.write("Secondary_ID", "elbow_shadow", 4)

-            # Set a velocity limit of 131 as advised by Trossen Robotics
-            # TODO(aliberts): remove as it's actually useless in position control
-            self.bus.write("Velocity_Limit", 131)
-
-            # Use 'extended position mode' for all motors except gripper, because in joint mode the servos
-            # can't rotate more than 360 degrees (from 0 to 4095) And some mistake can happen while assembling
-            # the arm, you could end up with a servo with a position 0 or 4095 at a crucial point.
-            # See: https://emanual.robotis.com/docs/en/dxl/x/x_series/#operating-mode11
            for motor in self.bus.motors:
-                if motor != "gripper":
-                    self.bus.write("Operating_Mode", motor, OperatingMode.EXTENDED_POSITION.value)
+                self.bus.write("Operating_Mode", motor, OperatingMode.EXTENDED_POSITION.value)

+            # TODO(pepijn): Re enable this
            # Use 'position control current based' for follower gripper to be limited by the limit of the
            # current. It can grasp an object without forcing too much even tho, it's goal position is a
            # complete grasp (both gripper fingers are ordered to join and reach a touch).
-            self.bus.write("Operating_Mode", "gripper", OperatingMode.CURRENT_POSITION.value)
+            # self.bus.write("Operating_Mode", "gripper", OperatingMode.CURRENT_POSITION.value)

    def get_observation(self) -> dict[str, Any]:
        """The returned observations do not have a batch dimension."""
        if not self.is_connected:
            raise DeviceNotConnectedError(f"{self} is not connected.")

-        obs_dict = {}
-
        # Read arm position
        start = time.perf_counter()
-        obs_dict[OBS_STATE] = self.bus.sync_read("Present_Position")
+        obs_dict = self.bus.sync_read("Present_Position")
        obs_dict = {f"{motor}.pos": val for motor, val in obs_dict.items()}
        dt_ms = (time.perf_counter() - start) * 1e3
        logger.debug(f"{self} read state: {dt_ms:.1f}ms")
@@ -21,7 +21,7 @@ You want to evaluate a model from the hub (eg: https://huggingface.co/lerobot/di
 for 10 episodes.

 ```
-python -m lerobot.scripts.eval \
+lerobot-eval \
    --policy.path=lerobot/diffusion_pusht \
    --env.type=pusht \
    --eval.batch_size=10 \
@@ -32,7 +32,7 @@ python -m lerobot.scripts.eval \

 OR, you want to evaluate a model checkpoint from the LeRobot training script for 10 episodes.
 ```
-python -m lerobot.scripts.eval \
+lerobot-eval \
    --policy.path=outputs/train/diffusion_pusht/checkpoints/005000/pretrained_model \
    --env.type=pusht \
    --eval.batch_size=10 \
@@ -302,11 +302,6 @@ class RobotClient:

                    self.logger.debug(f"Current latest action: {latest_action}")

-                    # Get queue state before changes
-                    old_size, old_timesteps = self._inspect_action_queue()
-                    if not old_timesteps:
-                        old_timesteps = [latest_action]  # queue was empty
-
                    # Get queue state before changes
                    old_size, old_timesteps = self._inspect_action_queue()
                    if not old_timesteps:
@@ -18,7 +18,7 @@ Helper to set motor ids and baudrate.
 Example:

 ```shell
-python -m lerobot.setup_motors \
+lerobot-setup-motors \
    --teleop.type=so100_leader \
    --teleop.port=/dev/tty.usbmodem575E0031751
 ```
@@ -18,7 +18,7 @@ Simple script to control a robot from teleoperation.
 Example:

 ```shell
-python -m lerobot.teleoperate \
+lerobot-teleoperate \
    --robot.type=so101_follower \
    --robot.port=/dev/tty.usbmodem58760431541 \
    --robot.cameras="{ front: {type: opencv, index_or_path: 0, width: 1920, height: 1080, fps: 30}}" \
@@ -32,7 +32,7 @@ python -m lerobot.teleoperate \
 Example teleoperation with bimanual so100:

 ```shell
-python -m lerobot.teleoperate \
+lerobot-teleoperate \
  --robot.type=bi_so100_follower \
  --robot.left_arm_port=/dev/tty.usbmodem5A460851411 \
  --robot.right_arm_port=/dev/tty.usbmodem5A460812391 \
@@ -0,0 +1,4 @@
+from .aloha_teleop import AlohaTeleop
+from .config_aloha_teleop import AlohaTeleopConfig
+
+__all__ = ["AlohaTeleop", "AlohaTeleopConfig"]
@@ -0,0 +1,125 @@
+#!/usr/bin/env python
+
+# Copyright 2024 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.
+
+import logging
+from functools import cached_property
+
+from lerobot.teleoperators.widowx.config_widowx import WidowXConfig
+from lerobot.teleoperators.widowx.widowx import WidowX
+
+from ..teleoperator import Teleoperator
+from .config_aloha_teleop import AlohaTeleopConfig
+
+logger = logging.getLogger(__name__)
+
+
+class AlohaTeleop(Teleoperator):
+    """
+    ALOHA Bimanual Teleoperator System using dual WidowX leader arms.
+    Based on the ALOHA (A Low-cost Open-source Hardware System for Bimanual Teleoperation) design.
+    """
+
+    config_class = AlohaTeleopConfig
+    name = "aloha_teleop"
+
+    def __init__(self, config: AlohaTeleopConfig):
+        super().__init__(config)
+        self.config = config
+
+        left_arm_config = WidowXConfig(
+            id=f"{config.id}_left" if config.id else None,
+            calibration_dir=config.calibration_dir,
+            port=config.left_arm_port,
+            gripper_motor=config.left_arm_gripper_motor,
+            use_degrees=config.left_arm_use_degrees,
+        )
+
+        right_arm_config = WidowXConfig(
+            id=f"{config.id}_right" if config.id else None,
+            calibration_dir=config.calibration_dir,
+            port=config.right_arm_port,
+            gripper_motor=config.right_arm_gripper_motor,
+            use_degrees=config.right_arm_use_degrees,
+        )
+
+        self.left_arm = WidowX(left_arm_config)
+        self.right_arm = WidowX(right_arm_config)
+
+    @cached_property
+    def action_features(self) -> dict[str, type]:
+        return {f"left_{motor}.pos": float for motor in self.left_arm.bus.motors} | {
+            f"right_{motor}.pos": float for motor in self.right_arm.bus.motors
+        }
+
+    @cached_property
+    def feedback_features(self) -> dict[str, type]:
+        return {}
+
+    @property
+    def is_connected(self) -> bool:
+        return self.left_arm.is_connected and self.right_arm.is_connected
+
+    def connect(self, calibrate: bool = True) -> None:
+        self.left_arm.connect(calibrate)
+        self.right_arm.connect(calibrate)
+
+    @property
+    def is_calibrated(self) -> bool:
+        return self.left_arm.is_calibrated and self.right_arm.is_calibrated
+
+    def calibrate(self) -> None:
+        self.left_arm.calibrate()
+        self.right_arm.calibrate()
+
+    def configure(self) -> None:
+        self.left_arm.configure()
+        self.right_arm.configure()
+
+    def setup_motors(self) -> None:
+        self.left_arm.setup_motors()
+        self.right_arm.setup_motors()
+
+    def get_action(self) -> dict[str, float]:
+        action_dict = {}
+
+        # Add "left_" prefix
+        left_action = self.left_arm.get_action()
+        action_dict.update({f"left_{key}": value for key, value in left_action.items()})
+
+        # Add "right_" prefix
+        right_action = self.right_arm.get_action()
+        action_dict.update({f"right_{key}": value for key, value in right_action.items()})
+
+        return action_dict
+
+    def send_feedback(self, feedback: dict[str, float]) -> None:
+        # Remove "left_" prefix
+        left_feedback = {
+            key.removeprefix("left_"): value for key, value in feedback.items() if key.startswith("left_")
+        }
+        # Remove "right_" prefix
+        right_feedback = {
+            key.removeprefix("right_"): value for key, value in feedback.items() if key.startswith("right_")
+        }
+
+        if left_feedback:
+            self.left_arm.send_feedback(left_feedback)
+        if right_feedback:
+            self.right_arm.send_feedback(right_feedback)
+
+    def disconnect(self) -> None:
+        self.left_arm.disconnect()
+        self.right_arm.disconnect()
@@ -0,0 +1,34 @@
+#!/usr/bin/env python
+
+# Copyright 2024 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 dataclasses import dataclass
+
+from ..config import TeleoperatorConfig
+
+
+@TeleoperatorConfig.register_subclass("aloha_teleop")
+@dataclass
+class AlohaTeleopConfig(TeleoperatorConfig):
+    left_arm_port: str
+    right_arm_port: str
+
+    # Parameters for left arm (WidowX)
+    left_arm_gripper_motor: str = "xl430-w250"
+    left_arm_use_degrees: bool = True
+
+    # Parameters for right arm (WidowX)
+    right_arm_gripper_motor: str = "xc430-w150"
+    right_arm_use_degrees: bool = True
@@ -88,6 +88,7 @@ class KochLeader(Teleoperator):
        return self.bus.is_calibrated

    def calibrate(self) -> None:
+        self.bus.disable_torque()
        if self.calibration:
            # Calibration file exists, ask user whether to use it or run new calibration
            user_input = input(
@@ -98,7 +99,6 @@ class KochLeader(Teleoperator):
                self.bus.write_calibration(self.calibration)
                return
        logger.info(f"\nRunning calibration of {self}")
-        self.bus.disable_torque()
        for motor in self.bus.motors:
            self.bus.write("Operating_Mode", motor, OperatingMode.EXTENDED_POSITION.value)

@@ -0,0 +1,25 @@
+#!/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 .config_reachy2_teleoperator import Reachy2TeleoperatorConfig
+from .reachy2_teleoperator import (
+    REACHY2_ANTENNAS_JOINTS,
+    REACHY2_L_ARM_JOINTS,
+    REACHY2_NECK_JOINTS,
+    REACHY2_R_ARM_JOINTS,
+    REACHY2_VEL,
+    Reachy2Teleoperator,
+)
@@ -0,0 +1,51 @@
+#!/usr/bin/env python
+
+# Copyright 2024 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 dataclasses import dataclass
+
+from ..config import TeleoperatorConfig
+
+
+@TeleoperatorConfig.register_subclass("reachy2_teleoperator")
+@dataclass
+class Reachy2TeleoperatorConfig(TeleoperatorConfig):
+    # IP address of the Reachy 2 robot used as teleoperator
+    ip_address: str | None = "localhost"
+
+    # Whether to use the present position of the joints as actions
+    # if False, the goal position of the joints will be used
+    use_present_position: bool = False
+
+    # Which parts of the robot to use
+    with_mobile_base: bool = True
+    with_l_arm: bool = True
+    with_r_arm: bool = True
+    with_neck: bool = True
+    with_antennas: bool = True
+
+    def __post_init__(self):
+        if not (
+            self.with_mobile_base
+            or self.with_l_arm
+            or self.with_r_arm
+            or self.with_neck
+            or self.with_antennas
+        ):
+            raise ValueError(
+                "No Reachy2Teleoperator part used.\n"
+                "At least one part of the robot must be set to True "
+                "(with_mobile_base, with_l_arm, with_r_arm, with_neck, with_antennas)"
+            )
@@ -0,0 +1,164 @@
+#!/usr/bin/env python
+
+# Copyright 2024 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.
+
+import logging
+import time
+
+from reachy2_sdk import ReachySDK
+
+from ..teleoperator import Teleoperator
+from .config_reachy2_teleoperator import Reachy2TeleoperatorConfig
+
+logger = logging.getLogger(__name__)
+
+# {lerobot_keys: reachy2_sdk_keys}
+REACHY2_NECK_JOINTS = {
+    "neck_yaw.pos": "head.neck.yaw",
+    "neck_pitch.pos": "head.neck.pitch",
+    "neck_roll.pos": "head.neck.roll",
+}
+
+REACHY2_ANTENNAS_JOINTS = {
+    "l_antenna.pos": "head.l_antenna",
+    "r_antenna.pos": "head.r_antenna",
+}
+
+REACHY2_R_ARM_JOINTS = {
+    "r_shoulder_pitch.pos": "r_arm.shoulder.pitch",
+    "r_shoulder_roll.pos": "r_arm.shoulder.roll",
+    "r_elbow_yaw.pos": "r_arm.elbow.yaw",
+    "r_elbow_pitch.pos": "r_arm.elbow.pitch",
+    "r_wrist_roll.pos": "r_arm.wrist.roll",
+    "r_wrist_pitch.pos": "r_arm.wrist.pitch",
+    "r_wrist_yaw.pos": "r_arm.wrist.yaw",
+    "r_gripper.pos": "r_arm.gripper",
+}
+
+REACHY2_L_ARM_JOINTS = {
+    "l_shoulder_pitch.pos": "l_arm.shoulder.pitch",
+    "l_shoulder_roll.pos": "l_arm.shoulder.roll",
+    "l_elbow_yaw.pos": "l_arm.elbow.yaw",
+    "l_elbow_pitch.pos": "l_arm.elbow.pitch",
+    "l_wrist_roll.pos": "l_arm.wrist.roll",
+    "l_wrist_pitch.pos": "l_arm.wrist.pitch",
+    "l_wrist_yaw.pos": "l_arm.wrist.yaw",
+    "l_gripper.pos": "l_arm.gripper",
+}
+
+REACHY2_VEL = {
+    "mobile_base.vx": "vx",
+    "mobile_base.vy": "vy",
+    "mobile_base.vtheta": "vtheta",
+}
+
+
+class Reachy2Teleoperator(Teleoperator):
+    """
+    [Reachy 2](https://www.pollen-robotics.com/reachy/), by Pollen Robotics.
+    """
+
+    config_class = Reachy2TeleoperatorConfig
+    name = "reachy2_specific"
+
+    def __init__(self, config: Reachy2TeleoperatorConfig):
+        super().__init__(config)
+        self.config = config
+        self.reachy: None | ReachySDK = None
+
+        self.joints_dict: dict[str, str] = self._generate_joints_dict()
+
+    def _generate_joints_dict(self) -> dict[str, str]:
+        joints = {}
+        if self.config.with_neck:
+            joints.update(REACHY2_NECK_JOINTS)
+        if self.config.with_l_arm:
+            joints.update(REACHY2_L_ARM_JOINTS)
+        if self.config.with_r_arm:
+            joints.update(REACHY2_R_ARM_JOINTS)
+        if self.config.with_antennas:
+            joints.update(REACHY2_ANTENNAS_JOINTS)
+        return joints
+
+    @property
+    def action_features(self) -> dict[str, type]:
+        if self.config.with_mobile_base:
+            return {
+                **dict.fromkeys(
+                    self.joints_dict.keys(),
+                    float,
+                ),
+                **dict.fromkeys(
+                    REACHY2_VEL.keys(),
+                    float,
+                ),
+            }
+        else:
+            return dict.fromkeys(self.joints_dict.keys(), float)
+
+    @property
+    def feedback_features(self) -> dict[str, type]:
+        return {}
+
+    @property
+    def is_connected(self) -> bool:
+        return self.reachy.is_connected() if self.reachy is not None else False
+
+    def connect(self, calibrate: bool = True) -> None:
+        self.reachy = ReachySDK(self.config.ip_address)
+        if not self.is_connected:
+            raise ConnectionError()
+        logger.info(f"{self} connected.")
+
+    @property
+    def is_calibrated(self) -> bool:
+        return True
+
+    def calibrate(self) -> None:
+        pass
+
+    def configure(self) -> None:
+        pass
+
+    def get_action(self) -> dict[str, float]:
+        start = time.perf_counter()
+
+        if self.reachy and self.is_connected:
+            if self.config.use_present_position:
+                joint_action = {
+                    k: self.reachy.joints[v].present_position for k, v in self.joints_dict.items()
+                }
+            else:
+                joint_action = {k: self.reachy.joints[v].goal_position for k, v in self.joints_dict.items()}
+
+            if not self.config.with_mobile_base:
+                dt_ms = (time.perf_counter() - start) * 1e3
+                logger.debug(f"{self} read action: {dt_ms:.1f}ms")
+                return joint_action
+
+            if self.config.use_present_position:
+                vel_action = {k: self.reachy.mobile_base.odometry[v] for k, v in REACHY2_VEL.items()}
+            else:
+                vel_action = {k: self.reachy.mobile_base.last_cmd_vel[v] for k, v in REACHY2_VEL.items()}
+        dt_ms = (time.perf_counter() - start) * 1e3
+        logger.debug(f"{self} read action: {dt_ms:.1f}ms")
+        return {**joint_action, **vel_action}
+
+    def send_feedback(self, feedback: dict[str, float]) -> None:
+        raise NotImplementedError
+
+    def disconnect(self) -> None:
+        if self.reachy and self.is_connected:
+            self.reachy.disconnect()
@@ -65,5 +65,9 @@ def make_teleoperator_from_config(config: TeleoperatorConfig) -> Teleoperator:
        from .bi_so100_leader import BiSO100Leader

        return BiSO100Leader(config)
+    elif config.type == "reachy2_teleoperator":
+        from .reachy2_teleoperator import Reachy2Teleoperator
+
+        return Reachy2Teleoperator(config)
    else:
        raise ValueError(config.type)
@@ -23,3 +23,7 @@ from ..config import TeleoperatorConfig
@dataclass
 class WidowXConfig(TeleoperatorConfig):
    port: str  # Port to connect to the arm
+
+    gripper_motor: str = "xl430-w250"  # This could be xc430-w150 or xl430-w250
+
+    use_degrees: bool = False
@@ -20,7 +20,6 @@ import time
 from lerobot.errors import DeviceAlreadyConnectedError, DeviceNotConnectedError
 from lerobot.motors import Motor, MotorCalibration, MotorNormMode
 from lerobot.motors.dynamixel import (
-    DriveMode,
    DynamixelMotorsBus,
    OperatingMode,
 )
@@ -40,22 +39,27 @@ class WidowX(Teleoperator):
    name = "widowx"

    def __init__(self, config: WidowXConfig):
-        raise NotImplementedError
        super().__init__(config)
        self.config = config
+        norm_mode_body = MotorNormMode.DEGREES if config.use_degrees else MotorNormMode.RANGE_M100_100
        self.bus = DynamixelMotorsBus(
            port=self.config.port,
            motors={
-                "waist": Motor(1, "xm430-w350", MotorNormMode.RANGE_M100_100),
-                "shoulder": Motor(2, "xm430-w350", MotorNormMode.RANGE_M100_100),
-                "shoulder_shadow": Motor(3, "xm430-w350", MotorNormMode.RANGE_M100_100),
-                "elbow": Motor(4, "xm430-w350", MotorNormMode.RANGE_M100_100),
-                "elbow_shadow": Motor(5, "xm430-w350", MotorNormMode.RANGE_M100_100),
-                "forearm_roll": Motor(6, "xm430-w350", MotorNormMode.RANGE_M100_100),
-                "wrist_angle": Motor(7, "xm430-w350", MotorNormMode.RANGE_M100_100),
-                "wrist_rotate": Motor(8, "xl430-w250", MotorNormMode.RANGE_M100_100),
-                "gripper": Motor(9, "xc430-w150", MotorNormMode.RANGE_0_100),
+                "waist": Motor(1, "xm430-w350", norm_mode_body),
+                "shoulder": Motor(2, "xm430-w350", norm_mode_body),
+                "shoulder_shadow": Motor(3, "xm430-w350", norm_mode_body),
+                "elbow": Motor(4, "xm430-w350", norm_mode_body),
+                "elbow_shadow": Motor(5, "xm430-w350", norm_mode_body),
+                "forearm_roll": Motor(6, "xm430-w350", norm_mode_body),
+                "wrist_angle": Motor(7, "xm430-w350", norm_mode_body),
+                "wrist_rotate": Motor(
+                    8, "xm430-w350", norm_mode_body
+                ),  # This could be xl430-w250 or xm430-w350
+                "gripper": Motor(
+                    9, self.config.gripper_motor, MotorNormMode.RANGE_0_100
+                ),  # This could be xc430-w150 or xl430-w250
            },
+            calibration=self.calibration,
        )

    @property
@@ -76,6 +80,9 @@ class WidowX(Teleoperator):

        self.bus.connect()
        if not self.is_calibrated and calibrate:
+            logger.info(
+                "Mismatch between calibration values in the motor and the calibration file or no calibration file found"
+            )
            self.calibrate()

        self.configure()
@@ -86,19 +93,27 @@ class WidowX(Teleoperator):
        return self.bus.is_calibrated

    def calibrate(self) -> None:
-        raise NotImplementedError  # TODO(aliberts): adapt code below (copied from koch)
-        logger.info(f"\nRunning calibration of {self}")
        self.bus.disable_torque()
+        if self.calibration:
+            # Calibration file exists, ask user whether to use it or run new calibration
+            user_input = input(
+                f"Press ENTER to use provided calibration file associated with the id {self.id}, or type 'c' and press ENTER to run calibration: "
+            )
+            if user_input.strip().lower() != "c":
+                logger.info(f"Writing calibration file associated with the id {self.id} to the motors")
+                self.bus.write_calibration(self.calibration)
+                return
+        logger.info(f"\nRunning calibration of {self}")
        for motor in self.bus.motors:
            self.bus.write("Operating_Mode", motor, OperatingMode.EXTENDED_POSITION.value)

-        self.bus.write("Drive_Mode", "elbow_flex", DriveMode.INVERTED.value)
-        drive_modes = {motor: 1 if motor == "elbow_flex" else 0 for motor in self.bus.motors}
+        # self.bus.write("Drive_Mode", "el", DriveMode.INVERTED.value)
+        # drive_modes = {motor: 1 if motor == ["elbow_shadow", "shoulder_shadow"] else 0 for motor in self.bus.motors}

-        input("Move robot to the middle of its range of motion and press ENTER....")
+        input(f"Move {self} to the middle of its range of motion and press ENTER....")
        homing_offsets = self.bus.set_half_turn_homings()

-        full_turn_motors = ["shoulder_pan", "wrist_roll"]
+        full_turn_motors = ["shoulder", "forearm_roll", "wrist_rotate"]
        unknown_range_motors = [motor for motor in self.bus.motors if motor not in full_turn_motors]
        print(
            f"Move all joints except {full_turn_motors} sequentially through their "
@@ -113,7 +128,7 @@ class WidowX(Teleoperator):
        for motor, m in self.bus.motors.items():
            self.calibration[motor] = MotorCalibration(
                id=m.id,
-                drive_mode=drive_modes[motor],
+                drive_mode=0,
                homing_offset=homing_offsets[motor],
                range_min=range_mins[motor],
                range_max=range_maxes[motor],
@@ -133,6 +148,22 @@ class WidowX(Teleoperator):
        self.bus.write("Secondary_ID", "shoulder_shadow", 2)
        self.bus.write("Secondary_ID", "elbow_shadow", 4)

+        for motor in self.bus.motors:
+            self.bus.write("Operating_Mode", motor, OperatingMode.EXTENDED_POSITION.value)
+
+        # TODO(pepijn): Re enable this
+        # Use 'position control current based' for gripper to be limited by the limit of the current.
+        # For the follower gripper, it means it can grasp an object without forcing too much even tho,
+        # its goal position is a complete grasp (both gripper fingers are ordered to join and reach a touch).
+        # For the leader gripper, it means we can use it as a physical trigger, since we can force with our finger
+        # to make it move, and it will move back to its original target position when we release the force.
+        # self.bus.write("Operating_Mode", "gripper", OperatingMode.CURRENT_POSITION.value)
+        # Set gripper's goal pos in current position mode so that we can use it as a trigger.
+        # self.bus.enable_torque("gripper")
+
+        if self.is_calibrated:
+            self.bus.write("Goal_Position", "gripper", self.config.gripper_open_pos)
+
    def get_action(self) -> dict[str, float]:
        if not self.is_connected:
            raise DeviceNotConnectedError(f"{self} is not connected.")
@@ -44,7 +44,7 @@ Below is the short version on how to train and run inference/eval:
 ### Train from scratch

 ```bash
-python -m lerobot.scripts.train \
+lerobot-train \
  --dataset.repo_id=${HF_USER}/<dataset> \
  --policy.type=act \
  --output_dir=outputs/train/<desired_policy_repo_id> \
@@ -59,7 +59,7 @@ _Writes checkpoints to `outputs/train/<desired_policy_repo_id>/checkpoints/`._
 ### Evaluate the policy/run inference

 ```bash
-python -m lerobot.record \
+lerobot-record \
  --robot.type=so100_follower \
  --dataset.repo_id=<hf_user>/eval_<dataset> \
  --policy.path=<hf_user>/<desired_policy_repo_id> \
@@ -17,10 +17,9 @@ import time


 def busy_wait(seconds):
-    if platform.system() == "Darwin":
-        # On Mac, `time.sleep` is not accurate and we need to use this while loop trick,
+    if platform.system() == "Darwin" or platform.system() == "Windows":
+        # On Mac and Windows, `time.sleep` is not accurate and we need to use this while loop trick,
        # but it consumes CPU cycles.
-        # TODO(rcadene): find an alternative: from python 11, time.sleep is precise
        end_time = time.perf_counter() + seconds
        while time.perf_counter() < end_time:
            pass
@@ -0,0 +1,177 @@
+#!/usr/bin/env python
+
+# Copyright 2024 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.
+
+import time
+from unittest.mock import MagicMock, patch
+
+import numpy as np
+import pytest
+
+from lerobot.cameras.reachy2_camera import Reachy2Camera, Reachy2CameraConfig
+from lerobot.errors import DeviceNotConnectedError
+
+PARAMS = [
+    ("teleop", "left"),
+    ("teleop", "right"),
+    ("depth", "rgb"),
+    # ("depth", "depth"),  # Depth camera is not available yet
+]
+
+
+def _make_cam_manager_mock():
+    c = MagicMock(name="CameraManagerMock")
+
+    teleop = MagicMock(name="TeleopCam")
+    teleop.width = 640
+    teleop.height = 480
+    teleop.get_frame = MagicMock(
+        side_effect=lambda *_, **__: (
+            np.zeros((480, 640, 3), dtype=np.uint8),
+            time.time(),
+        )
+    )
+
+    depth = MagicMock(name="DepthCam")
+    depth.width = 640
+    depth.height = 480
+    depth.get_frame = MagicMock(
+        side_effect=lambda *_, **__: (
+            np.zeros((480, 640, 3), dtype=np.uint8),
+            time.time(),
+        )
+    )
+
+    c.is_connected.return_value = True
+    c.teleop = teleop
+    c.depth = depth
+
+    def _connect():
+        c.teleop = teleop
+        c.depth = depth
+        c.is_connected.return_value = True
+
+    def _disconnect():
+        c.teleop = None
+        c.depth = None
+        c.is_connected.return_value = False
+
+    c.connect = MagicMock(side_effect=_connect)
+    c.disconnect = MagicMock(side_effect=_disconnect)
+
+    # Mock methods
+    c.initialize_cameras = MagicMock()
+
+    return c
+
+
+@pytest.fixture(
+    params=PARAMS,
+    # ids=["teleop-left", "teleop-right", "torso-rgb", "torso-depth"],
+    ids=["teleop-left", "teleop-right", "torso-rgb"],
+)
+def camera(request):
+    name, image_type = request.param
+    with (
+        patch(
+            "lerobot.cameras.reachy2_camera.reachy2_camera.CameraManager",
+            side_effect=lambda *a, **k: _make_cam_manager_mock(),
+        ),
+    ):
+        config = Reachy2CameraConfig(name=name, image_type=image_type)
+        cam = Reachy2Camera(config)
+        yield cam
+        if cam.is_connected:
+            cam.disconnect()
+
+
+def test_connect(camera):
+    camera.connect()
+    assert camera.is_connected
+    camera.cam_manager.initialize_cameras.assert_called_once()
+
+
+def test_read(camera):
+    camera.connect()
+
+    img = camera.read()
+    if camera.config.name == "teleop":
+        camera.cam_manager.teleop.get_frame.assert_called_once()
+    elif camera.config.name == "depth":
+        camera.cam_manager.depth.get_frame.assert_called_once()
+    assert isinstance(img, np.ndarray)
+    assert img.shape == (480, 640, 3)
+
+
+def test_disconnect(camera):
+    camera.connect()
+
+    camera.disconnect()
+    assert not camera.is_connected
+
+
+def test_async_read(camera):
+    camera.connect()
+    try:
+        img = camera.async_read()
+
+        assert camera.thread is not None
+        assert camera.thread.is_alive()
+        assert isinstance(img, np.ndarray)
+    finally:
+        if camera.is_connected:
+            camera.disconnect()
+
+
+def test_async_read_timeout(camera):
+    camera.connect()
+    try:
+        with pytest.raises(TimeoutError):
+            camera.async_read(timeout_ms=0)
+    finally:
+        if camera.is_connected:
+            camera.disconnect()
+
+
+def test_read_before_connect(camera):
+    with pytest.raises(DeviceNotConnectedError):
+        _ = camera.read()
+
+
+def test_disconnect_before_connect(camera):
+    with pytest.raises(DeviceNotConnectedError):
+        camera.disconnect()
+
+
+def test_async_read_before_connect(camera):
+    with pytest.raises(DeviceNotConnectedError):
+        _ = camera.async_read()
+
+
+def test_wrong_camera_name():
+    with pytest.raises(ValueError):
+        _ = Reachy2CameraConfig(name="wrong-name", image_type="left")
+
+
+def test_wrong_image_type():
+    with pytest.raises(ValueError):
+        _ = Reachy2CameraConfig(name="teleop", image_type="rgb")
+    with pytest.raises(ValueError):
+        _ = Reachy2CameraConfig(name="depth", image_type="left")
+
+
+def test_wrong_color_mode():
+    with pytest.raises(ValueError):
+        _ = Reachy2CameraConfig(name="teleop", image_type="left", color_mode="wrong-color")
@@ -28,6 +28,7 @@ pytest_plugins = [
    "tests.fixtures.files",
    "tests.fixtures.hub",
    "tests.fixtures.optimizers",
+    "tests.plugins.reachy2_sdk",
 ]


@@ -0,0 +1,30 @@
+import sys
+import types
+from unittest.mock import MagicMock
+
+
+def _install_reachy2_sdk_stub():
+    sdk = types.ModuleType("reachy2_sdk")
+    sdk.__path__ = []
+    sdk.ReachySDK = MagicMock(name="ReachySDK")
+
+    media = types.ModuleType("reachy2_sdk.media")
+    media.__path__ = []
+    camera = types.ModuleType("reachy2_sdk.media.camera")
+    camera.CameraView = MagicMock(name="CameraView")
+    camera_manager = types.ModuleType("reachy2_sdk.media.camera_manager")
+    camera_manager.CameraManager = MagicMock(name="CameraManager")
+
+    sdk.media = media
+    media.camera = camera
+    media.camera_manager = camera_manager
+
+    # Register in sys.modules
+    sys.modules.setdefault("reachy2_sdk", sdk)
+    sys.modules.setdefault("reachy2_sdk.media", media)
+    sys.modules.setdefault("reachy2_sdk.media.camera", camera)
+    sys.modules.setdefault("reachy2_sdk.media.camera_manager", camera_manager)
+
+
+def pytest_sessionstart(session):
+    _install_reachy2_sdk_stub()
@@ -0,0 +1,326 @@
+#!/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 unittest.mock import MagicMock, patch
+
+import numpy as np
+import pytest
+
+from lerobot.robots.reachy2 import (
+    REACHY2_ANTENNAS_JOINTS,
+    REACHY2_L_ARM_JOINTS,
+    REACHY2_NECK_JOINTS,
+    REACHY2_R_ARM_JOINTS,
+    REACHY2_VEL,
+    Reachy2Robot,
+    Reachy2RobotConfig,
+)
+
+# {lerobot_keys: reachy2_sdk_keys}
+REACHY2_JOINTS = {
+    **REACHY2_NECK_JOINTS,
+    **REACHY2_ANTENNAS_JOINTS,
+    **REACHY2_R_ARM_JOINTS,
+    **REACHY2_L_ARM_JOINTS,
+}
+
+PARAMS = [
+    {},  # default config
+    {"with_mobile_base": False},
+    {"with_mobile_base": False, "with_l_arm": False, "with_antennas": False},
+    {"with_r_arm": False, "with_neck": False, "with_antennas": False},
+    {"use_external_commands": True, "disable_torque_on_disconnect": True},
+    {"use_external_commands": True, "with_mobile_base": False, "with_neck": False},
+    {"disable_torque_on_disconnect": False},
+    {"max_relative_target": 5},
+    {"with_right_teleop_camera": False},
+    {"with_left_teleop_camera": False, "with_right_teleop_camera": False},
+    {"with_left_teleop_camera": False, "with_torso_camera": True},
+]
+
+
+def _make_reachy2_sdk_mock():
+    class JointSpy:
+        __slots__ = (
+            "present_position",
+            "_goal_position",
+            "_on_set",
+        )
+
+        def __init__(self, present_position=0.0, on_set=None):
+            self.present_position = present_position
+            self._goal_position = present_position
+            self._on_set = on_set
+
+        @property
+        def goal_position(self):
+            return self._goal_position
+
+        @goal_position.setter
+        def goal_position(self, v):
+            self._goal_position = v
+            if self._on_set:
+                self._on_set()
+
+    r = MagicMock(name="ReachySDKMock")
+    r.is_connected.return_value = True
+
+    def _connect():
+        r.is_connected.return_value = True
+
+    def _disconnect():
+        r.is_connected.return_value = False
+
+    # Global counter of goal_position sets
+    r._goal_position_set_total = 0
+
+    def _on_any_goal_set():
+        r._goal_position_set_total += 1
+
+    # Mock joints with some dummy positions
+    joints = {
+        k: JointSpy(
+            present_position=float(i),
+            on_set=_on_any_goal_set,
+        )
+        for i, k in enumerate(REACHY2_JOINTS.values())
+    }
+    r.joints = joints
+
+    # Mock mobile base with some dummy odometry
+    r.mobile_base = MagicMock()
+    r.mobile_base.odometry = {
+        "x": 0.1,
+        "y": -0.2,
+        "theta": 21.3,
+        "vx": 0.001,
+        "vy": 0.002,
+        "vtheta": 0.0,
+    }
+
+    r.connect = MagicMock(side_effect=_connect)
+    r.disconnect = MagicMock(side_effect=_disconnect)
+
+    # Mock methods
+    r.turn_on = MagicMock()
+    r.reset_default_limits = MagicMock()
+    r.send_goal_positions = MagicMock()
+    r.turn_off_smoothly = MagicMock()
+    r.mobile_base.set_goal_speed = MagicMock()
+    r.mobile_base.send_speed_command = MagicMock()
+
+    return r
+
+
+def _make_reachy2_camera_mock(*args, **kwargs):
+    cfg = args[0] if args else kwargs.get("config")
+    name = getattr(cfg, "name", kwargs.get("name", "cam"))
+    image_type = getattr(cfg, "image_type", kwargs.get("image_type", "cam"))
+    width = getattr(cfg, "width", kwargs.get("width", 640))
+    height = getattr(cfg, "height", kwargs.get("height", 480))
+
+    cam = MagicMock(name=f"Reachy2CameraMock:{name}")
+    cam.name = name
+    cam.image_type = image_type
+    cam.width = width
+    cam.height = height
+    cam.connect = MagicMock()
+    cam.disconnect = MagicMock()
+    cam.async_read = MagicMock(side_effect=lambda: np.zeros((height, width, 3), dtype=np.uint8))
+    return cam
+
+
+@pytest.fixture(params=PARAMS, ids=lambda p: "default" if not p else ",".join(p.keys()))
+def reachy2(request):
+    with (
+        patch(
+            "lerobot.robots.reachy2.robot_reachy2.ReachySDK",
+            side_effect=lambda *a, **k: _make_reachy2_sdk_mock(),
+        ),
+        patch(
+            "lerobot.cameras.reachy2_camera.reachy2_camera.Reachy2Camera",
+            side_effect=_make_reachy2_camera_mock,
+        ),
+    ):
+        overrides = request.param
+        cfg = Reachy2RobotConfig(ip_address="192.168.0.200", **overrides)
+        robot = Reachy2Robot(cfg)
+        yield robot
+        if robot.is_connected:
+            robot.disconnect()
+
+
+def test_connect_disconnect(reachy2):
+    assert not reachy2.is_connected
+
+    reachy2.connect()
+    assert reachy2.is_connected
+
+    reachy2.reachy.turn_on.assert_called_once()
+    reachy2.reachy.reset_default_limits.assert_called_once()
+
+    reachy2.disconnect()
+    assert not reachy2.is_connected
+
+    if reachy2.config.disable_torque_on_disconnect:
+        reachy2.reachy.turn_off_smoothly.assert_called_once()
+    else:
+        reachy2.reachy.turn_off_smoothly.assert_not_called()
+    reachy2.reachy.disconnect.assert_called_once()
+
+
+def test_get_joints_dict(reachy2):
+    reachy2.connect()
+
+    if reachy2.config.with_neck:
+        assert "neck_yaw.pos" in reachy2.joints_dict
+        assert "neck_pitch.pos" in reachy2.joints_dict
+        assert "neck_roll.pos" in reachy2.joints_dict
+    else:
+        assert "neck_yaw.pos" not in reachy2.joints_dict
+        assert "neck_pitch.pos" not in reachy2.joints_dict
+        assert "neck_roll.pos" not in reachy2.joints_dict
+
+    if reachy2.config.with_antennas:
+        assert "l_antenna.pos" in reachy2.joints_dict
+        assert "r_antenna.pos" in reachy2.joints_dict
+    else:
+        assert "l_antenna.pos" not in reachy2.joints_dict
+        assert "r_antenna.pos" not in reachy2.joints_dict
+
+    if reachy2.config.with_r_arm:
+        assert "r_shoulder_pitch.pos" in reachy2.joints_dict
+        assert "r_shoulder_roll.pos" in reachy2.joints_dict
+        assert "r_elbow_yaw.pos" in reachy2.joints_dict
+        assert "r_elbow_pitch.pos" in reachy2.joints_dict
+        assert "r_wrist_roll.pos" in reachy2.joints_dict
+        assert "r_wrist_pitch.pos" in reachy2.joints_dict
+        assert "r_wrist_yaw.pos" in reachy2.joints_dict
+        assert "r_gripper.pos" in reachy2.joints_dict
+    else:
+        assert "r_shoulder_pitch.pos" not in reachy2.joints_dict
+        assert "r_shoulder_roll.pos" not in reachy2.joints_dict
+        assert "r_elbow_yaw.pos" not in reachy2.joints_dict
+        assert "r_elbow_pitch.pos" not in reachy2.joints_dict
+        assert "r_wrist_roll.pos" not in reachy2.joints_dict
+        assert "r_wrist_pitch.pos" not in reachy2.joints_dict
+        assert "r_wrist_yaw.pos" not in reachy2.joints_dict
+        assert "r_gripper.pos" not in reachy2.joints_dict
+
+    if reachy2.config.with_l_arm:
+        assert "l_shoulder_pitch.pos" in reachy2.joints_dict
+        assert "l_shoulder_roll.pos" in reachy2.joints_dict
+        assert "l_elbow_yaw.pos" in reachy2.joints_dict
+        assert "l_elbow_pitch.pos" in reachy2.joints_dict
+        assert "l_wrist_roll.pos" in reachy2.joints_dict
+        assert "l_wrist_pitch.pos" in reachy2.joints_dict
+        assert "l_wrist_yaw.pos" in reachy2.joints_dict
+        assert "l_gripper.pos" in reachy2.joints_dict
+    else:
+        assert "l_shoulder_pitch.pos" not in reachy2.joints_dict
+        assert "l_shoulder_roll.pos" not in reachy2.joints_dict
+        assert "l_elbow_yaw.pos" not in reachy2.joints_dict
+        assert "l_elbow_pitch.pos" not in reachy2.joints_dict
+        assert "l_wrist_roll.pos" not in reachy2.joints_dict
+        assert "l_wrist_pitch.pos" not in reachy2.joints_dict
+        assert "l_wrist_yaw.pos" not in reachy2.joints_dict
+        assert "l_gripper.pos" not in reachy2.joints_dict
+
+
+def test_get_observation(reachy2):
+    reachy2.connect()
+    obs = reachy2.get_observation()
+
+    expected_keys = set(reachy2.joints_dict)
+    expected_keys.update(f"{v}" for v in REACHY2_VEL.keys() if reachy2.config.with_mobile_base)
+    expected_keys.update(reachy2.cameras.keys())
+    assert set(obs.keys()) == expected_keys
+
+    for motor in reachy2.joints_dict.keys():
+        assert obs[motor] == reachy2.reachy.joints[REACHY2_JOINTS[motor]].present_position
+    if reachy2.config.with_mobile_base:
+        for vel in REACHY2_VEL.keys():
+            assert obs[vel] == reachy2.reachy.mobile_base.odometry[REACHY2_VEL[vel]]
+    if reachy2.config.with_left_teleop_camera:
+        assert obs["teleop_left"].shape == (
+            reachy2.config.cameras["teleop_left"].height,
+            reachy2.config.cameras["teleop_left"].width,
+            3,
+        )
+    if reachy2.config.with_right_teleop_camera:
+        assert obs["teleop_right"].shape == (
+            reachy2.config.cameras["teleop_right"].height,
+            reachy2.config.cameras["teleop_right"].width,
+            3,
+        )
+    if reachy2.config.with_torso_camera:
+        assert obs["torso_rgb"].shape == (
+            reachy2.config.cameras["torso_rgb"].height,
+            reachy2.config.cameras["torso_rgb"].width,
+            3,
+        )
+
+
+def test_send_action(reachy2):
+    reachy2.connect()
+
+    action = {k: i * 10.0 for i, k in enumerate(reachy2.joints_dict.keys(), start=1)}
+    if reachy2.config.with_mobile_base:
+        action.update({k: i * 0.1 for i, k in enumerate(REACHY2_VEL.keys(), start=1)})
+
+    previous_present_position = {
+        k: reachy2.reachy.joints[REACHY2_JOINTS[k]].present_position for k in reachy2.joints_dict.keys()
+    }
+    returned = reachy2.send_action(action)
+
+    if reachy2.config.max_relative_target is None:
+        assert returned == action
+
+    assert reachy2.reachy._goal_position_set_total == len(reachy2.joints_dict)
+    for motor in reachy2.joints_dict.keys():
+        expected_pos = action[motor]
+        real_pos = reachy2.reachy.joints[REACHY2_JOINTS[motor]].goal_position
+        if reachy2.config.max_relative_target is None:
+            assert real_pos == expected_pos
+        else:
+            assert real_pos == previous_present_position[motor] + np.sign(expected_pos) * min(
+                abs(expected_pos - real_pos), reachy2.config.max_relative_target
+            )
+
+    if reachy2.config.with_mobile_base:
+        goal_speed = [i * 0.1 for i, _ in enumerate(REACHY2_VEL.keys(), start=1)]
+        reachy2.reachy.mobile_base.set_goal_speed.assert_called_once_with(*goal_speed)
+
+    if reachy2.config.use_external_commands:
+        reachy2.reachy.send_goal_positions.assert_not_called()
+        if reachy2.config.with_mobile_base:
+            reachy2.reachy.mobile_base.send_speed_command.assert_not_called()
+    else:
+        reachy2.reachy.send_goal_positions.assert_called_once()
+        if reachy2.config.with_mobile_base:
+            reachy2.reachy.mobile_base.send_speed_command.assert_called_once()
+
+
+def test_no_part_declared():
+    with pytest.raises(ValueError):
+        _ = Reachy2RobotConfig(
+            ip_address="192.168.0.200",
+            with_mobile_base=False,
+            with_l_arm=False,
+            with_r_arm=False,
+            with_neck=False,
+            with_antennas=False,
+        )
@@ -0,0 +1,150 @@
+#!/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 unittest.mock import MagicMock, patch
+
+import pytest
+
+from lerobot.teleoperators.reachy2_teleoperator import (
+    REACHY2_ANTENNAS_JOINTS,
+    REACHY2_L_ARM_JOINTS,
+    REACHY2_NECK_JOINTS,
+    REACHY2_R_ARM_JOINTS,
+    REACHY2_VEL,
+    Reachy2Teleoperator,
+    Reachy2TeleoperatorConfig,
+)
+
+# {lerobot_keys: reachy2_sdk_keys}
+REACHY2_JOINTS = {
+    **REACHY2_NECK_JOINTS,
+    **REACHY2_ANTENNAS_JOINTS,
+    **REACHY2_R_ARM_JOINTS,
+    **REACHY2_L_ARM_JOINTS,
+}
+
+PARAMS = [
+    {},  # default config
+    {"with_mobile_base": False},
+    {"with_mobile_base": False, "with_l_arm": False, "with_antennas": False},
+    {"with_r_arm": False, "with_neck": False, "with_antennas": False},
+    {"with_mobile_base": False, "with_neck": False},
+    {"use_present_position": True},
+]
+
+
+def _make_reachy2_sdk_mock():
+    r = MagicMock(name="ReachySDKMock")
+    r.is_connected.return_value = True
+
+    def _connect():
+        r.is_connected.return_value = True
+
+    def _disconnect():
+        r.is_connected.return_value = False
+
+    # Mock joints with some dummy positions
+    joints = {
+        k: MagicMock(
+            present_position=float(i),
+            goal_position=float(i) + 0.5,
+        )
+        for i, k in enumerate(REACHY2_JOINTS.values())
+    }
+    r.joints = joints
+
+    # Mock mobile base with some dummy odometry
+    r.mobile_base = MagicMock()
+    r.mobile_base.last_cmd_vel = {
+        "vx": -0.2,
+        "vy": 0.2,
+        "vtheta": 11.0,
+    }
+    r.mobile_base.odometry = {
+        "x": 1.0,
+        "y": 2.0,
+        "theta": 20.0,
+        "vx": 0.1,
+        "vy": -0.1,
+        "vtheta": 8.0,
+    }
+
+    r.connect = MagicMock(side_effect=_connect)
+    r.disconnect = MagicMock(side_effect=_disconnect)
+
+    return r
+
+
+@pytest.fixture(params=PARAMS, ids=lambda p: "default" if not p else ",".join(p.keys()))
+def reachy2(request):
+    with (
+        patch(
+            "lerobot.teleoperators.reachy2_teleoperator.reachy2_teleoperator.ReachySDK",
+            side_effect=lambda *a, **k: _make_reachy2_sdk_mock(),
+        ),
+    ):
+        overrides = request.param
+        cfg = Reachy2TeleoperatorConfig(ip_address="192.168.0.200", **overrides)
+        robot = Reachy2Teleoperator(cfg)
+        yield robot
+        if robot.is_connected:
+            robot.disconnect()
+
+
+def test_connect_disconnect(reachy2):
+    assert not reachy2.is_connected
+
+    reachy2.connect()
+    assert reachy2.is_connected
+
+    reachy2.disconnect()
+    assert not reachy2.is_connected
+
+    reachy2.reachy.disconnect.assert_called_once()
+
+
+def test_get_action(reachy2):
+    reachy2.connect()
+    action = reachy2.get_action()
+
+    expected_keys = set(reachy2.joints_dict)
+    expected_keys.update(f"{v}" for v in REACHY2_VEL.keys() if reachy2.config.with_mobile_base)
+    assert set(action.keys()) == expected_keys
+
+    for motor in reachy2.joints_dict.keys():
+        if reachy2.config.use_present_position:
+            assert action[motor] == reachy2.reachy.joints[REACHY2_JOINTS[motor]].present_position
+        else:
+            assert action[motor] == reachy2.reachy.joints[REACHY2_JOINTS[motor]].goal_position
+    if reachy2.config.with_mobile_base:
+        if reachy2.config.use_present_position:
+            for vel in REACHY2_VEL.keys():
+                assert action[vel] == reachy2.reachy.mobile_base.odometry[REACHY2_VEL[vel]]
+        else:
+            for vel in REACHY2_VEL.keys():
+                assert action[vel] == reachy2.reachy.mobile_base.last_cmd_vel[REACHY2_VEL[vel]]
+
+
+def test_no_part_declared():
+    with pytest.raises(ValueError):
+        _ = Reachy2TeleoperatorConfig(
+            ip_address="192.168.0.200",
+            with_mobile_base=False,
+            with_l_arm=False,
+            with_r_arm=False,
+            with_neck=False,
+            with_antennas=False,
+        )
Author	SHA1	Message	Date
Pepijn	ed773219c0	add resume	2025-09-14 14:06:15 +02:00
Pepijn	a075669184	add aloha setup	2025-09-14 12:45:08 +02:00
Pepijn	bc953e4b5a	add degree to aloha	2025-09-13 21:17:51 +02:00
Pepijn	6b62113515	match koch follower and robot as much as possible	2025-09-11 16:11:01 +02:00
Steven Palma	d602e8169c	fix(scripts): revert deletion of rs cam config import introduced by #1767 (#1876 )	2025-09-08 18:29:39 +02:00
Steven Gong	49baccdccb	Disable torque before applying calibration logic (#1889 )	2025-09-08 11:38:13 +02:00
Gaëlle Lannuzel	6a3d57031a	2 add reachy 2 to updated lerobot (#1767 ) * Start adding Reachy 2 (no camera) * Fix joint shape * Remove print * Modify observation_features * Fix observation state * Try adding a fake Reachy teleoperator * Saving test scripts * Add reachy2camera to cameras * Add teleop_left camera to observation * Create test_reachy2_camera.py * Update utils.py * Add all rgb cameras * Future depth work * Try adding mobile_base velocity * Update tests * Update data_acquisition_server.py * Update with use_external_commands * Replay * Usable with or without mobile base * No need for new isntance * Use same ip for cameras * Remove useless imports * Add resume * Divide joints in multiple dicts * Divide joinits into several dicts in teleoperator * Fix forgotten method call * Create test_robot_client.py * Open gripper on start * Add arguments for cameras * Modify get_frame() requested size * Call generate_joints_dict on _init_ * black + isort * Add reachy2 in imports * Add reachy2 dependencies * Add documentation * Update reachy2.mdx * Update reachy2.mdx * Clean files and add types * Fix type in send_action * Remove print * Delete test files * Clean code * Update cameras * Disconnect from camera * Run pre-commit hooks * Update pyproject.toml * Create test_reachy2.py * Fix generate_joints * Update test_reachy2.py * Update send_action test * Update reachy2_cameras depth + CameraManager * Update reachy2_camera tests * Remove useless import and args * Rename reachy2_teleoperator * Create test_reachy2_teleoperator.py * Fix remainging fake_teleoperator * Remove useless elements * Mock cameras in test_reachy2 * Delete commented lines * Add use_present_position to teleoperator * Add cameras tests * Add check no part + test * Use disable_torque_on_disconnect * Use odometry for vel with present_position * Update documentation * Fix vel value type * Use ensure_safe_goal_position * Import joints dict from classes * Update reachy2.mdx * Update reachy2.mdx * Update minimal version * Update minimal version * fix(tests) fixes for reachy2 tests; removing reachy2 references from the script * Add reachy2_sdk fake as plugins --------- Co-authored-by: Michel Aractingi <michel.aractingi@huggingface.co>	2025-09-05 11:03:14 +02:00
Justin Huang	d74494d92b	Allow max_relative_target to be a float (#1837 ) * Remove unused max_relative_target for stretch3 * Fix type annotation and allow integer max_relative_target values * Configure max_relative_target to be floats instead of ints * Update docs and types to reflect that max_relative_target can be a dict * Remove unnecessary isinstance check for ints * Fix typo in name --------- Co-authored-by: Justin Huang <justin.huang@jpl.nasa.gov>	2025-09-05 09:58:47 +02:00
Pepijn	882c80d446	Lower limits by 50% for current and torque for gripper motor (#1809 ) Signed-off-by: Pepijn <138571049+pkooij@users.noreply.github.com>	2025-08-29 16:06:55 +02:00
Pepijn	61b0eeae4b	Add feetech firmware update docs (#1793 ) * Add feetech firmware update docs * add bonus * formatting * adapt text * feedback pr	2025-08-28 11:18:54 +02:00
mgiac-hexagon	577cd10974	Removed dupicate lines of code (#1709 )	2025-08-25 12:39:32 +02:00
lxk	b0923ab74b	fix(dataset): Use provided episode_data in save_episode (#1740 ) The 'episode_data' parameter was previously ignored, causing an error if provided. This change ensures it is correctly used, which allows for asynchronous episode saving by passing a copy of the episode buffer, preventing conflicts with the main data collection loop.	2025-08-22 15:24:02 +02:00
Jack Vial	7f70b78f32	Add missing encoding table entries for Koch arm (#1534 )	2025-08-20 17:24:05 +02:00
Steven Palma	55198de096	fix(ci): rename libegl1-mesa in deb13 trixie (#1735 )	2025-08-14 11:12:06 +02:00
Steven Palma	0878c6880f	fix(ci): inverted names (#1705 )	2025-08-09 00:21:42 +02:00
Caroline Pascal	11e6bd762a	fix(busy_wait): fix busy_wait implementation for Windows platforms and removing erronous TODO (#1695 )	2025-08-08 10:46:14 +02:00
Steven Palma	ce3b9f627e	chore(docs): prioritize use of entry points in docs + fix nightly badge (#1692 ) * chore(docs): fix typo in nightly badge * chore(docs): prioritize the use of entrypoints for consistency	2025-08-07 14:25:44 +02:00