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lerobot/docs/source/reachy2.mdx
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Caroline Pascal bd9619dfc3 feat(encoding parameters): adding support for user provided video encoding parameters (#3455)
* chore(video backend): renaming codec into video_backend in get_safe_default_video_backend()

* feat(pyav utils): adding suport for PyAV encoding parameters validation

* feat(VideoEncoderConfig): creating a VideoEncoderConfig to encapsulate encoding parameters

* feat(VideoEncoderConfig): propagating the VideoEncoderConfig in the codebase

* chore(docs): updating the docs

* feat(metadata): adding encoding parameters in dataset metadata

* fix(concatenation compatibility): adding compatibility check when concatenating video files

* feat(VideoEncoderConfig init): making VideoEncoderConfig more robust and adaptable to multiple backends

* feat(pyav checks): making pyav parameters checks more robust

* chore(duplicate): removing duplicate get_codec_options definition

* test(existing): adapting existing tests

* test(new): adding new tests for encoding related features

* chore(format): fixing formatting issues

* chore(PyAV): cleaning up PyAV utils and encoding parameters checks to stick to the minimun required tooling.

* chore(format): formatting code

* chore(doctrings): updating docstrings

* fix(camera_encoder_config): Removing camera_encoder_config from LeRobotDataset, as it's only required in LeRobotDatasetWriter.

* feat(default values): applying a consistent naming convention for default RGB cameras video encoder parameters

* fix(rollout): propagating VideoEncoderConfig to the latest recording modes

* chore(format): formatting code, fixing error messages and variable names

* fix(arguments order): reverting changes in arguments order in StreamingVideoEncoder

* chore(relative imports): switching to relative local imports within lerobot.datasets

* test(artifacts): cleaning up artifacts for the video encoding tests

* chore(docs): updating docs

* chore(fromat): formatting code

* fix(imports): refactoring the file architecture to avoid circular imports. VideoEncoderConfig is now defined in lerobot.configs and lazily imports av at runtime.

* fix(typos): fixing typos and small mistakes

* test(factories): updating factories

* feat(aggregate): updating dataset aggregation procedure. Encoding tuning paramters (crf, g,...) are ignored for validation and changed to None in the aggregated dataset if incompatible.

* docs(typos): fixing typos

* fix(deletion): reverting unwanted deletion

* fix(typos): fixing multiple typos

* feat(codec options): passing codec options to lerobot_edit_dataset episode deletion tool

* typo(typo): typo

* fix(typos): fixing remaining typos

* chore(rename): renaming camera_encoder_config to camera_encoder

* docs(clean): cleaning and formating docs

* docs(dataset): addind details about datasets

* chore(format): formatting code

* docs(warning): adding warning regarding encoding parameters modification

* fix(re-encoding): removing inconsistent re-encoding option in lerobot_edit_dataset

* typos(typos): typos

* chore(format): resolving prettier issues

* fix(h264_nvenc): fixing crf handling for h264_nvenc

* docs(clean): removing too technical parts of the docs

* fix(imports): fixing imports at the __init__ level

* fix(imports): fixing not very pretty imports in video config file
2026-05-14 23:46:42 +02:00

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# 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 "$HOME/.reachy.log":/home/reachy/.ros/log \
-v /usr/lib/x86_64-linux-gnu:/opt/host-libs \
--entrypoint /package/launch.sh \
pollenrobotics/reachy2_core:1.7.5.9_deploy \
start_rviz:=true start_sdk_server:=true mujoco:=true
```
> [!NOTE]
> If MuJoCo runs slowly (low simulation frequency), append `-e LD_LIBRARY_PATH="/opt/host-libs:$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. Youre 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 robots motions.
- **Using LeRobots record script**: LeRobot owns session control and decides when to start/stop episodes. If you also use the VR teleop app, its 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 LeRobots 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
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 \
--robot.with_torso_camera=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 \
--dataset.streaming_encoding=true \
--dataset.encoder_threads=2 \
# --dataset.camera_encoder.vcodec=auto \
--display_data=true
```
#### Specific Options
**Extended setup overview (all options included):**
```bash
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.camera_width=640 \
--robot.camera_height=480 \
--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 \
--dataset.streaming_encoding=true \
--dataset.encoder_threads=2 \
# --dataset.camera_encoder.vcodec=auto \
--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:
```bash
--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.
```bash
--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**. Enable or disable each camera with default parameters using:
```bash
--robot.with_left_teleop_camera=<true|false> \
--robot.with_right_teleop_camera=<true|false> \
--robot.with_torso_camera=<true|false>
```
By default, no camera is recorded, all camera arguments are set to `false`.
If you want to, you can use custom `width` and `height` parameters for Reachy 2's cameras using the `--robot.camera_width` & `--robot.camera_height` argument:
```bash
--robot.camera_width=1920 \
--robot.camera_height=1080
```
This will change the resolution of all 3 default robot cameras (enabled by the above bool arguments).
If you want, you can add additional cameras other than the ones in the robot as usual with:
```bash
--robot.cameras="{ extra: {type: opencv, index_or_path: 42, width: 640, height: 480, fps: 30}}" \
```
## Step 2: Replay
Make sure the robot is configured with the same parts as the dataset:
```bash
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
```
## Step 3: Train
```bash
lerobot-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
lerobot-eval \
--robot.type=reachy2 \
--robot.ip_address=192.168.0.200 \
--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
```