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Author SHA1 Message Date
Michel Aractingi 4dbd63f613 remove dead comment 2025-09-04 15:32:11 +02:00
Michel Aractingi 873cafef39 Downgrade the version of grpc and protobuf to fix the conflicting requirements of reachy2_sdk
Update automatically generated proto files
2025-09-04 15:31:21 +02:00
glannuzel 1c9ee16b1d Update reachy2.mdx 2025-09-03 17:49:40 +02:00
glannuzel 1e0bf5732c Update reachy2.mdx 2025-09-03 14:55:22 +02:00
glannuzel a539ccb92c Import joints dict from classes 2025-09-03 12:42:47 +02:00
glannuzel bc88445eae Use ensure_safe_goal_position 2025-09-01 11:31:48 +02:00
glannuzel 5a0f1c032c Fix vel value type 2025-08-28 19:43:36 +02:00
glannuzel 4f277a7c43 Update documentation 2025-08-28 19:18:48 +02:00
glannuzel d023e33cd8 Use odometry for vel with present_position 2025-08-28 18:40:05 +02:00
glannuzel 5264feecef Use disable_torque_on_disconnect 2025-08-28 17:55:30 +02:00
glannuzel 67843db756 Add check no part + test 2025-08-28 17:44:23 +02:00
glannuzel 8e8ebe3732 Add cameras tests 2025-08-28 15:33:56 +02:00
glannuzel f31acfd67f Add use_present_position to teleoperator 2025-08-28 15:15:05 +02:00
glannuzel b31b512954 Delete commented lines 2025-08-27 12:55:00 +02:00
glannuzel 95efab22eb Mock cameras in test_reachy2 2025-08-27 12:52:17 +02:00
glannuzel 3225aeb287 Remove useless elements 2025-08-27 12:13:53 +02:00
glannuzel 128d39fbe5 Fix remainging fake_teleoperator 2025-08-27 12:12:37 +02:00
glannuzel d5adffa289 Create test_reachy2_teleoperator.py 2025-08-27 11:25:34 +02:00
glannuzel 42d11c20c2 Rename reachy2_teleoperator 2025-08-27 11:25:28 +02:00
glannuzel 8b59d28610 Remove useless import and args 2025-08-26 18:40:40 +02:00
glannuzel 9281649228 Update reachy2_camera tests 2025-08-26 18:35:44 +02:00
glannuzel 4259c38856 Update reachy2_cameras depth + CameraManager 2025-08-26 18:35:31 +02:00
glannuzel ecca518072 Update send_action test 2025-08-26 16:31:52 +02:00
glannuzel 31117fcf94 Update test_reachy2.py 2025-08-26 16:04:45 +02:00
glannuzel 56807e772f Fix generate_joints 2025-08-26 16:04:33 +02:00
glannuzel ecad00e0cd Create test_reachy2.py 2025-08-26 13:01:02 +02:00
glannuzel 32ddf7d46e Update pyproject.toml 2025-08-26 11:28:49 +02:00
glannuzel 6560f47d15 Run pre-commit hooks 2025-08-22 10:42:27 +02:00
glannuzel fd75203cfa Disconnect from camera 2025-08-21 18:03:30 +02:00
glannuzel fc6b709da0 Update cameras 2025-08-21 17:34:35 +02:00
glannuzel b07c3b271c Clean code 2025-08-21 15:06:12 +02:00
glannuzel 67acccf778 Delete test files 2025-08-21 15:00:53 +02:00
glannuzel 130a6a969b Merge remote-tracking branch 'upstream/main' into update-lerobot 2025-08-21 14:58:12 +02:00
glannuzel ffaaa63af6 Remove print 2025-08-21 14:55:56 +02:00
glannuzel bdf2e0b71c Fix type in send_action 2025-08-21 14:46:55 +02:00
Jack Vial 7f70b78f32 Add missing encoding table entries for Koch arm (#1534) 2025-08-20 17:24:05 +02:00
glannuzel 60c342ad2d Clean files and add types 2025-08-19 15:26:41 +02:00
glannuzel 6e6031bb37 Update reachy2.mdx 2025-08-18 17:45:11 +02:00
glannuzel b32ece5e20 Update reachy2.mdx 2025-08-18 17:27:50 +02:00
glannuzel e3ed212295 Add documentation 2025-08-14 17:31:07 +02:00
Steven Palma 55198de096 fix(ci): rename libegl1-mesa in deb13 trixie (#1735) 2025-08-14 11:12:06 +02:00
glannuzel bdb566201e Add reachy2 dependencies 2025-08-13 13:34:09 +02:00
glannuzel b23a882ccc Add reachy2 in imports 2025-08-13 11:54:09 +02:00
glannuzel d855bc4f4f black + isort 2025-08-11 17:51:01 +02:00
Gaëlle Lannuzel 58be04d46d Merge pull request #7 from pollen-robotics/6-choose-cameras-in-config
6 choose cameras in config
2025-08-11 17:40:08 +02:00
glannuzel 44cdd5ac90 Call generate_joints_dict on _init_ 2025-08-11 17:38:25 +02:00
glannuzel ab6bbd68a7 Modify get_frame() requested size 2025-08-11 17:37:58 +02:00
glannuzel 0c8b0a7cf0 Add arguments for cameras 2025-08-11 17:37:42 +02:00
Gaëlle Lannuzel 091fbd824e Merge pull request #5 from pollen-robotics/separate-parts-in-config
Separate parts in config
2025-08-11 10:22:32 +02:00
glannuzel 2379c3607a Open gripper on start 2025-08-11 10:13:08 +02:00
Steven Palma 0878c6880f fix(ci): inverted names (#1705) 2025-08-09 00:21:42 +02:00
glannuzel 146403afc1 Create test_robot_client.py 2025-08-08 18:41:17 +02:00
glannuzel 674996db96 Fix forgotten method call 2025-08-08 16:40:22 +02:00
glannuzel cba73399f1 Divide joinits into several dicts in teleoperator 2025-08-08 14:22:49 +02:00
glannuzel 8236f7b52b Divide joints in multiple dicts 2025-08-08 14:19:18 +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
glannuzel 20f5f45ac2 Add resume 2025-08-07 11:29:15 +02:00
glannuzel 33b6a4ddcd Remove useless imports 2025-08-06 14:08:07 +02:00
glannuzel f9b8be5730 Use same ip for cameras 2025-08-06 13:52:39 +02:00
glannuzel 346d4950c5 No need for new isntance 2025-08-06 13:27:25 +02:00
glannuzel 75652a39b4 Usable with or without mobile base 2025-08-06 13:15:03 +02:00
glannuzel ee406bdfbf Replay 2025-08-06 11:45:12 +02:00
glannuzel 58b6dd0f73 Update with use_external_commands 2025-08-06 11:44:42 +02:00
glannuzel 6cc6fb36f4 Update data_acquisition_server.py 2025-08-05 12:42:24 +02:00
glannuzel 8217f44235 Update tests 2025-08-04 16:28:42 +02:00
glannuzel ddaca00801 Try adding mobile_base velocity 2025-07-29 15:12:05 +02:00
glannuzel 096cdeb8ad Future depth work 2025-07-29 14:40:10 +02:00
glannuzel 042e34898a Add all rgb cameras 2025-07-29 14:25:15 +02:00
glannuzel c9dc12106f Update utils.py 2025-07-29 14:07:48 +02:00
glannuzel 9735606cbb Create test_reachy2_camera.py 2025-07-29 14:07:39 +02:00
glannuzel 18e7232f88 Add teleop_left camera to observation 2025-07-29 14:07:26 +02:00
glannuzel 8b9fc0d2e9 Add reachy2camera to cameras 2025-07-29 14:06:57 +02:00
glannuzel 08c47eac4b Saving test scripts 2025-07-29 10:26:03 +02:00
glannuzel 8de5610273 Try adding a fake Reachy teleoperator 2025-07-29 10:24:50 +02:00
glannuzel 6acb6bd3e5 Fix observation state 2025-07-29 10:18:47 +02:00
glannuzel 32b08a242d Modify observation_features 2025-07-28 17:59:14 +02:00
glannuzel 2d646fbc64 Remove print 2025-07-28 17:18:43 +02:00
glannuzel 40cb84c005 Fix joint shape 2025-07-28 17:18:00 +02:00
glannuzel 0800406d2b Start adding Reachy 2 (no camera) 2025-07-28 16:37:48 +02:00
Gaëlle Lannuzel 4a1233306b Merge pull request #3 from huggingface/main
Update LeRobot
2025-07-28 10:51:15 +02:00
55 changed files with 2143 additions and 199 deletions
+1 -1
View File
@@ -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
+2 -2
View File
@@ -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:
+9 -9
View File
@@ -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 -6
View File
@@ -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.
+1 -1
View File
@@ -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 \
+2
View File
@@ -35,6 +35,8 @@
title: Koch v1.1
- local: lekiwi
title: LeKiwi
- local: reachy2
title: Reachy 2
title: "Robots"
- sections:
- local: notebooks
+1 -1
View File
@@ -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:
+2 -2
View File
@@ -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**:
+11 -11
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@@ -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 \
+8 -8
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@@ -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}}" \
+2 -2
View File
@@ -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 \
+5 -5
View File
@@ -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
+4 -4
View File
@@ -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
+287
View File
@@ -0,0 +1,287 @@
# 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. 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:**
```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
```
+3 -3
View File
@@ -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
+5 -5
View File
@@ -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
+5 -5
View File
@@ -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
+14 -14
View File
@@ -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 \
+1 -1
View File
@@ -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 \
+3 -1
View File
@@ -96,7 +96,7 @@ dependencies = [
pygame-dep = ["pygame>=2.5.1"]
placo-dep = ["placo>=0.9.6"]
transformers-dep = ["transformers>=4.50.3,<4.52.0"] # TODO: Bumb dependency
grpcio-dep = ["grpcio==1.73.1", "protobuf==6.31.0"]
grpcio-dep = ["grpcio==1.70.0", "protobuf==5.29.5"]
# Motors
feetech = ["feetech-servo-sdk>=1.0.0"]
@@ -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>=1.0.12"]
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]",
+1 -1
View File
@@ -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
+2 -3
View File
@@ -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 +1,77 @@
# 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
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()
+7 -1
View File
@@ -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
+1 -1
View File
@@ -20,7 +20,7 @@ Helper to find the camera devices available in your system.
Example:
```shell
python -m lerobot.find_cameras
lerobot-find-cameras
```
"""
+1 -1
View File
@@ -18,7 +18,7 @@ Helper to find the USB port associated with your MotorsBus.
Example:
```shell
python -m lerobot.find_port
lerobot-find-port
```
"""
+2
View File
@@ -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],
+2 -2
View File
@@ -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
+2 -2
View File
@@ -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 \
+4 -2
View File
@@ -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 \
@@ -83,6 +83,7 @@ from lerobot.robots import ( # noqa: F401
hope_jr,
koch_follower,
make_robot_from_config,
reachy2,
so100_follower,
so101_follower,
)
@@ -93,6 +94,7 @@ from lerobot.teleoperators import ( # noqa: F401
homunculus,
koch_leader,
make_teleoperator_from_config,
reachy2_teleoperator,
so100_leader,
so101_leader,
)
+3 -2
View File
@@ -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,
)
+25
View File
@@ -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)"
)
+230
View File
@@ -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()
+4
View File
@@ -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
+2 -2
View File
@@ -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 \
+2 -2
View File
@@ -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 \
+1 -1
View File
@@ -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
```
+2 -2
View File
@@ -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 +1,25 @@
#!/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()
+4
View File
@@ -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)
@@ -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> \
+28 -27
View File
@@ -1,7 +1,8 @@
# -*- coding: utf-8 -*-
# Generated by the protocol buffer compiler. DO NOT EDIT!
# NO CHECKED-IN PROTOBUF GENCODE
# source: lerobot/transport/services.proto
# Protobuf Python Version: 6.31.0
# source: services.proto
# Protobuf Python Version: 5.29.0
"""Generated protocol buffer code."""
from google.protobuf import descriptor as _descriptor
from google.protobuf import descriptor_pool as _descriptor_pool
@@ -10,11 +11,11 @@ from google.protobuf import symbol_database as _symbol_database
from google.protobuf.internal import builder as _builder
_runtime_version.ValidateProtobufRuntimeVersion(
_runtime_version.Domain.PUBLIC,
6,
31,
5,
29,
0,
'',
'lerobot/transport/services.proto'
'services.proto'
)
# @@protoc_insertion_point(imports)
@@ -23,31 +24,31 @@ _sym_db = _symbol_database.Default()
DESCRIPTOR = _descriptor_pool.Default().AddSerializedFile(b'\n lerobot/transport/services.proto\x12\ttransport\"L\n\nTransition\x12\x30\n\x0etransfer_state\x18\x01 \x01(\x0e\x32\x18.transport.TransferState\x12\x0c\n\x04\x64\x61ta\x18\x02 \x01(\x0c\"L\n\nParameters\x12\x30\n\x0etransfer_state\x18\x01 \x01(\x0e\x32\x18.transport.TransferState\x12\x0c\n\x04\x64\x61ta\x18\x02 \x01(\x0c\"T\n\x12InteractionMessage\x12\x30\n\x0etransfer_state\x18\x01 \x01(\x0e\x32\x18.transport.TransferState\x12\x0c\n\x04\x64\x61ta\x18\x02 \x01(\x0c\"M\n\x0bObservation\x12\x30\n\x0etransfer_state\x18\x01 \x01(\x0e\x32\x18.transport.TransferState\x12\x0c\n\x04\x64\x61ta\x18\x02 \x01(\x0c\"\x17\n\x07\x41\x63tions\x12\x0c\n\x04\x64\x61ta\x18\x01 \x01(\x0c\"\x1b\n\x0bPolicySetup\x12\x0c\n\x04\x64\x61ta\x18\x01 \x01(\x0c\"\x07\n\x05\x45mpty*`\n\rTransferState\x12\x14\n\x10TRANSFER_UNKNOWN\x10\x00\x12\x12\n\x0eTRANSFER_BEGIN\x10\x01\x12\x13\n\x0fTRANSFER_MIDDLE\x10\x02\x12\x10\n\x0cTRANSFER_END\x10\x03\x32\x81\x02\n\x0eLearnerService\x12=\n\x10StreamParameters\x12\x10.transport.Empty\x1a\x15.transport.Parameters0\x01\x12<\n\x0fSendTransitions\x12\x15.transport.Transition\x1a\x10.transport.Empty(\x01\x12\x45\n\x10SendInteractions\x12\x1d.transport.InteractionMessage\x1a\x10.transport.Empty(\x01\x12+\n\x05Ready\x12\x10.transport.Empty\x1a\x10.transport.Empty2\xf5\x01\n\x0e\x41syncInference\x12>\n\x10SendObservations\x12\x16.transport.Observation\x1a\x10.transport.Empty(\x01\x12\x32\n\nGetActions\x12\x10.transport.Empty\x1a\x12.transport.Actions\x12\x42\n\x16SendPolicyInstructions\x12\x16.transport.PolicySetup\x1a\x10.transport.Empty\x12+\n\x05Ready\x12\x10.transport.Empty\x1a\x10.transport.Emptyb\x06proto3')
DESCRIPTOR = _descriptor_pool.Default().AddSerializedFile(b'\n\x0eservices.proto\x12\ttransport\"L\n\nTransition\x12\x30\n\x0etransfer_state\x18\x01 \x01(\x0e\x32\x18.transport.TransferState\x12\x0c\n\x04\x64\x61ta\x18\x02 \x01(\x0c\"L\n\nParameters\x12\x30\n\x0etransfer_state\x18\x01 \x01(\x0e\x32\x18.transport.TransferState\x12\x0c\n\x04\x64\x61ta\x18\x02 \x01(\x0c\"T\n\x12InteractionMessage\x12\x30\n\x0etransfer_state\x18\x01 \x01(\x0e\x32\x18.transport.TransferState\x12\x0c\n\x04\x64\x61ta\x18\x02 \x01(\x0c\"M\n\x0bObservation\x12\x30\n\x0etransfer_state\x18\x01 \x01(\x0e\x32\x18.transport.TransferState\x12\x0c\n\x04\x64\x61ta\x18\x02 \x01(\x0c\"\x17\n\x07\x41\x63tions\x12\x0c\n\x04\x64\x61ta\x18\x01 \x01(\x0c\"\x1b\n\x0bPolicySetup\x12\x0c\n\x04\x64\x61ta\x18\x01 \x01(\x0c\"\x07\n\x05\x45mpty*`\n\rTransferState\x12\x14\n\x10TRANSFER_UNKNOWN\x10\x00\x12\x12\n\x0eTRANSFER_BEGIN\x10\x01\x12\x13\n\x0fTRANSFER_MIDDLE\x10\x02\x12\x10\n\x0cTRANSFER_END\x10\x03\x32\x81\x02\n\x0eLearnerService\x12=\n\x10StreamParameters\x12\x10.transport.Empty\x1a\x15.transport.Parameters0\x01\x12<\n\x0fSendTransitions\x12\x15.transport.Transition\x1a\x10.transport.Empty(\x01\x12\x45\n\x10SendInteractions\x12\x1d.transport.InteractionMessage\x1a\x10.transport.Empty(\x01\x12+\n\x05Ready\x12\x10.transport.Empty\x1a\x10.transport.Empty2\xf5\x01\n\x0e\x41syncInference\x12>\n\x10SendObservations\x12\x16.transport.Observation\x1a\x10.transport.Empty(\x01\x12\x32\n\nGetActions\x12\x10.transport.Empty\x1a\x12.transport.Actions\x12\x42\n\x16SendPolicyInstructions\x12\x16.transport.PolicySetup\x1a\x10.transport.Empty\x12+\n\x05Ready\x12\x10.transport.Empty\x1a\x10.transport.Emptyb\x06proto3')
_globals = globals()
_builder.BuildMessageAndEnumDescriptors(DESCRIPTOR, _globals)
_builder.BuildTopDescriptorsAndMessages(DESCRIPTOR, 'lerobot.transport.services_pb2', _globals)
_builder.BuildTopDescriptorsAndMessages(DESCRIPTOR, 'services_pb2', _globals)
if not _descriptor._USE_C_DESCRIPTORS:
DESCRIPTOR._loaded_options = None
_globals['_TRANSFERSTATE']._serialized_start=431
_globals['_TRANSFERSTATE']._serialized_end=527
_globals['_TRANSITION']._serialized_start=47
_globals['_TRANSITION']._serialized_end=123
_globals['_PARAMETERS']._serialized_start=125
_globals['_PARAMETERS']._serialized_end=201
_globals['_INTERACTIONMESSAGE']._serialized_start=203
_globals['_INTERACTIONMESSAGE']._serialized_end=287
_globals['_OBSERVATION']._serialized_start=289
_globals['_OBSERVATION']._serialized_end=366
_globals['_ACTIONS']._serialized_start=368
_globals['_ACTIONS']._serialized_end=391
_globals['_POLICYSETUP']._serialized_start=393
_globals['_POLICYSETUP']._serialized_end=420
_globals['_EMPTY']._serialized_start=422
_globals['_EMPTY']._serialized_end=429
_globals['_LEARNERSERVICE']._serialized_start=530
_globals['_LEARNERSERVICE']._serialized_end=787
_globals['_ASYNCINFERENCE']._serialized_start=790
_globals['_ASYNCINFERENCE']._serialized_end=1035
_globals['_TRANSFERSTATE']._serialized_start=413
_globals['_TRANSFERSTATE']._serialized_end=509
_globals['_TRANSITION']._serialized_start=29
_globals['_TRANSITION']._serialized_end=105
_globals['_PARAMETERS']._serialized_start=107
_globals['_PARAMETERS']._serialized_end=183
_globals['_INTERACTIONMESSAGE']._serialized_start=185
_globals['_INTERACTIONMESSAGE']._serialized_end=269
_globals['_OBSERVATION']._serialized_start=271
_globals['_OBSERVATION']._serialized_end=348
_globals['_ACTIONS']._serialized_start=350
_globals['_ACTIONS']._serialized_end=373
_globals['_POLICYSETUP']._serialized_start=375
_globals['_POLICYSETUP']._serialized_end=402
_globals['_EMPTY']._serialized_start=404
_globals['_EMPTY']._serialized_end=411
_globals['_LEARNERSERVICE']._serialized_start=512
_globals['_LEARNERSERVICE']._serialized_end=769
_globals['_ASYNCINFERENCE']._serialized_start=772
_globals['_ASYNCINFERENCE']._serialized_end=1017
# @@protoc_insertion_point(module_scope)
+57 -57
View File
@@ -3,9 +3,9 @@
import grpc
import warnings
from lerobot.transport import services_pb2 as lerobot_dot_transport_dot_services__pb2
import services_pb2 as services__pb2
GRPC_GENERATED_VERSION = '1.73.1'
GRPC_GENERATED_VERSION = '1.70.0'
GRPC_VERSION = grpc.__version__
_version_not_supported = False
@@ -18,14 +18,14 @@ except ImportError:
if _version_not_supported:
raise RuntimeError(
f'The grpc package installed is at version {GRPC_VERSION},'
+ f' but the generated code in lerobot/transport/services_pb2_grpc.py depends on'
+ f' but the generated code in services_pb2_grpc.py depends on'
+ f' grpcio>={GRPC_GENERATED_VERSION}.'
+ f' Please upgrade your grpc module to grpcio>={GRPC_GENERATED_VERSION}'
+ f' or downgrade your generated code using grpcio-tools<={GRPC_VERSION}.'
)
class LearnerServiceStub:
class LearnerServiceStub(object):
"""LearnerService: the Actor calls this to push transitions.
The Learner implements this service.
"""
@@ -38,27 +38,27 @@ class LearnerServiceStub:
"""
self.StreamParameters = channel.unary_stream(
'/transport.LearnerService/StreamParameters',
request_serializer=lerobot_dot_transport_dot_services__pb2.Empty.SerializeToString,
response_deserializer=lerobot_dot_transport_dot_services__pb2.Parameters.FromString,
request_serializer=services__pb2.Empty.SerializeToString,
response_deserializer=services__pb2.Parameters.FromString,
_registered_method=True)
self.SendTransitions = channel.stream_unary(
'/transport.LearnerService/SendTransitions',
request_serializer=lerobot_dot_transport_dot_services__pb2.Transition.SerializeToString,
response_deserializer=lerobot_dot_transport_dot_services__pb2.Empty.FromString,
request_serializer=services__pb2.Transition.SerializeToString,
response_deserializer=services__pb2.Empty.FromString,
_registered_method=True)
self.SendInteractions = channel.stream_unary(
'/transport.LearnerService/SendInteractions',
request_serializer=lerobot_dot_transport_dot_services__pb2.InteractionMessage.SerializeToString,
response_deserializer=lerobot_dot_transport_dot_services__pb2.Empty.FromString,
request_serializer=services__pb2.InteractionMessage.SerializeToString,
response_deserializer=services__pb2.Empty.FromString,
_registered_method=True)
self.Ready = channel.unary_unary(
'/transport.LearnerService/Ready',
request_serializer=lerobot_dot_transport_dot_services__pb2.Empty.SerializeToString,
response_deserializer=lerobot_dot_transport_dot_services__pb2.Empty.FromString,
request_serializer=services__pb2.Empty.SerializeToString,
response_deserializer=services__pb2.Empty.FromString,
_registered_method=True)
class LearnerServiceServicer:
class LearnerServiceServicer(object):
"""LearnerService: the Actor calls this to push transitions.
The Learner implements this service.
"""
@@ -93,23 +93,23 @@ def add_LearnerServiceServicer_to_server(servicer, server):
rpc_method_handlers = {
'StreamParameters': grpc.unary_stream_rpc_method_handler(
servicer.StreamParameters,
request_deserializer=lerobot_dot_transport_dot_services__pb2.Empty.FromString,
response_serializer=lerobot_dot_transport_dot_services__pb2.Parameters.SerializeToString,
request_deserializer=services__pb2.Empty.FromString,
response_serializer=services__pb2.Parameters.SerializeToString,
),
'SendTransitions': grpc.stream_unary_rpc_method_handler(
servicer.SendTransitions,
request_deserializer=lerobot_dot_transport_dot_services__pb2.Transition.FromString,
response_serializer=lerobot_dot_transport_dot_services__pb2.Empty.SerializeToString,
request_deserializer=services__pb2.Transition.FromString,
response_serializer=services__pb2.Empty.SerializeToString,
),
'SendInteractions': grpc.stream_unary_rpc_method_handler(
servicer.SendInteractions,
request_deserializer=lerobot_dot_transport_dot_services__pb2.InteractionMessage.FromString,
response_serializer=lerobot_dot_transport_dot_services__pb2.Empty.SerializeToString,
request_deserializer=services__pb2.InteractionMessage.FromString,
response_serializer=services__pb2.Empty.SerializeToString,
),
'Ready': grpc.unary_unary_rpc_method_handler(
servicer.Ready,
request_deserializer=lerobot_dot_transport_dot_services__pb2.Empty.FromString,
response_serializer=lerobot_dot_transport_dot_services__pb2.Empty.SerializeToString,
request_deserializer=services__pb2.Empty.FromString,
response_serializer=services__pb2.Empty.SerializeToString,
),
}
generic_handler = grpc.method_handlers_generic_handler(
@@ -119,7 +119,7 @@ def add_LearnerServiceServicer_to_server(servicer, server):
# This class is part of an EXPERIMENTAL API.
class LearnerService:
class LearnerService(object):
"""LearnerService: the Actor calls this to push transitions.
The Learner implements this service.
"""
@@ -139,8 +139,8 @@ class LearnerService:
request,
target,
'/transport.LearnerService/StreamParameters',
lerobot_dot_transport_dot_services__pb2.Empty.SerializeToString,
lerobot_dot_transport_dot_services__pb2.Parameters.FromString,
services__pb2.Empty.SerializeToString,
services__pb2.Parameters.FromString,
options,
channel_credentials,
insecure,
@@ -166,8 +166,8 @@ class LearnerService:
request_iterator,
target,
'/transport.LearnerService/SendTransitions',
lerobot_dot_transport_dot_services__pb2.Transition.SerializeToString,
lerobot_dot_transport_dot_services__pb2.Empty.FromString,
services__pb2.Transition.SerializeToString,
services__pb2.Empty.FromString,
options,
channel_credentials,
insecure,
@@ -193,8 +193,8 @@ class LearnerService:
request_iterator,
target,
'/transport.LearnerService/SendInteractions',
lerobot_dot_transport_dot_services__pb2.InteractionMessage.SerializeToString,
lerobot_dot_transport_dot_services__pb2.Empty.FromString,
services__pb2.InteractionMessage.SerializeToString,
services__pb2.Empty.FromString,
options,
channel_credentials,
insecure,
@@ -220,8 +220,8 @@ class LearnerService:
request,
target,
'/transport.LearnerService/Ready',
lerobot_dot_transport_dot_services__pb2.Empty.SerializeToString,
lerobot_dot_transport_dot_services__pb2.Empty.FromString,
services__pb2.Empty.SerializeToString,
services__pb2.Empty.FromString,
options,
channel_credentials,
insecure,
@@ -233,7 +233,7 @@ class LearnerService:
_registered_method=True)
class AsyncInferenceStub:
class AsyncInferenceStub(object):
"""AsyncInference: from Robot perspective
Robot send observations to & executes action received from a remote Policy server
"""
@@ -246,27 +246,27 @@ class AsyncInferenceStub:
"""
self.SendObservations = channel.stream_unary(
'/transport.AsyncInference/SendObservations',
request_serializer=lerobot_dot_transport_dot_services__pb2.Observation.SerializeToString,
response_deserializer=lerobot_dot_transport_dot_services__pb2.Empty.FromString,
request_serializer=services__pb2.Observation.SerializeToString,
response_deserializer=services__pb2.Empty.FromString,
_registered_method=True)
self.GetActions = channel.unary_unary(
'/transport.AsyncInference/GetActions',
request_serializer=lerobot_dot_transport_dot_services__pb2.Empty.SerializeToString,
response_deserializer=lerobot_dot_transport_dot_services__pb2.Actions.FromString,
request_serializer=services__pb2.Empty.SerializeToString,
response_deserializer=services__pb2.Actions.FromString,
_registered_method=True)
self.SendPolicyInstructions = channel.unary_unary(
'/transport.AsyncInference/SendPolicyInstructions',
request_serializer=lerobot_dot_transport_dot_services__pb2.PolicySetup.SerializeToString,
response_deserializer=lerobot_dot_transport_dot_services__pb2.Empty.FromString,
request_serializer=services__pb2.PolicySetup.SerializeToString,
response_deserializer=services__pb2.Empty.FromString,
_registered_method=True)
self.Ready = channel.unary_unary(
'/transport.AsyncInference/Ready',
request_serializer=lerobot_dot_transport_dot_services__pb2.Empty.SerializeToString,
response_deserializer=lerobot_dot_transport_dot_services__pb2.Empty.FromString,
request_serializer=services__pb2.Empty.SerializeToString,
response_deserializer=services__pb2.Empty.FromString,
_registered_method=True)
class AsyncInferenceServicer:
class AsyncInferenceServicer(object):
"""AsyncInference: from Robot perspective
Robot send observations to & executes action received from a remote Policy server
"""
@@ -302,23 +302,23 @@ def add_AsyncInferenceServicer_to_server(servicer, server):
rpc_method_handlers = {
'SendObservations': grpc.stream_unary_rpc_method_handler(
servicer.SendObservations,
request_deserializer=lerobot_dot_transport_dot_services__pb2.Observation.FromString,
response_serializer=lerobot_dot_transport_dot_services__pb2.Empty.SerializeToString,
request_deserializer=services__pb2.Observation.FromString,
response_serializer=services__pb2.Empty.SerializeToString,
),
'GetActions': grpc.unary_unary_rpc_method_handler(
servicer.GetActions,
request_deserializer=lerobot_dot_transport_dot_services__pb2.Empty.FromString,
response_serializer=lerobot_dot_transport_dot_services__pb2.Actions.SerializeToString,
request_deserializer=services__pb2.Empty.FromString,
response_serializer=services__pb2.Actions.SerializeToString,
),
'SendPolicyInstructions': grpc.unary_unary_rpc_method_handler(
servicer.SendPolicyInstructions,
request_deserializer=lerobot_dot_transport_dot_services__pb2.PolicySetup.FromString,
response_serializer=lerobot_dot_transport_dot_services__pb2.Empty.SerializeToString,
request_deserializer=services__pb2.PolicySetup.FromString,
response_serializer=services__pb2.Empty.SerializeToString,
),
'Ready': grpc.unary_unary_rpc_method_handler(
servicer.Ready,
request_deserializer=lerobot_dot_transport_dot_services__pb2.Empty.FromString,
response_serializer=lerobot_dot_transport_dot_services__pb2.Empty.SerializeToString,
request_deserializer=services__pb2.Empty.FromString,
response_serializer=services__pb2.Empty.SerializeToString,
),
}
generic_handler = grpc.method_handlers_generic_handler(
@@ -328,7 +328,7 @@ def add_AsyncInferenceServicer_to_server(servicer, server):
# This class is part of an EXPERIMENTAL API.
class AsyncInference:
class AsyncInference(object):
"""AsyncInference: from Robot perspective
Robot send observations to & executes action received from a remote Policy server
"""
@@ -348,8 +348,8 @@ class AsyncInference:
request_iterator,
target,
'/transport.AsyncInference/SendObservations',
lerobot_dot_transport_dot_services__pb2.Observation.SerializeToString,
lerobot_dot_transport_dot_services__pb2.Empty.FromString,
services__pb2.Observation.SerializeToString,
services__pb2.Empty.FromString,
options,
channel_credentials,
insecure,
@@ -375,8 +375,8 @@ class AsyncInference:
request,
target,
'/transport.AsyncInference/GetActions',
lerobot_dot_transport_dot_services__pb2.Empty.SerializeToString,
lerobot_dot_transport_dot_services__pb2.Actions.FromString,
services__pb2.Empty.SerializeToString,
services__pb2.Actions.FromString,
options,
channel_credentials,
insecure,
@@ -402,8 +402,8 @@ class AsyncInference:
request,
target,
'/transport.AsyncInference/SendPolicyInstructions',
lerobot_dot_transport_dot_services__pb2.PolicySetup.SerializeToString,
lerobot_dot_transport_dot_services__pb2.Empty.FromString,
services__pb2.PolicySetup.SerializeToString,
services__pb2.Empty.FromString,
options,
channel_credentials,
insecure,
@@ -429,8 +429,8 @@ class AsyncInference:
request,
target,
'/transport.AsyncInference/Ready',
lerobot_dot_transport_dot_services__pb2.Empty.SerializeToString,
lerobot_dot_transport_dot_services__pb2.Empty.FromString,
services__pb2.Empty.SerializeToString,
services__pb2.Empty.FromString,
options,
channel_credentials,
insecure,
+2 -3
View File
@@ -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
+177
View File
@@ -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")
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#!/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,
)