> For the complete documentation index, see [llms.txt](https://tk233.gitbook.io/notes/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://tk233.gitbook.io/notes/ml-rl/rl-frameworks/case-study-getting-started-with-lerobot.md). # Case Study: Getting Started with LeRobot {% embed url="" %} ```bash conda activate lerobot ``` Grant permission ```bash sudo nano /etc/udev/rules.d/50-lerobot.rules ``` {% code title="50-lerobot.rules" overflow="wrap" %} ```bash SUBSYSTEMS=="usb", ATTRS{idVendor}=="1a86", ATTRS{idProduct}=="55d3", GROUP="users", MODE="0666" ``` {% endcode %} ```bash sudo udevadm control --reload-rules sudo udevadm trigger ``` Teleoperation demo ```bash python lerobot/scripts/control_robot.py teleoperate \ --robot-path lerobot/configs/robot/koch.yaml ``` Login to hugging face ```bash huggingface-cli login --token ${HUGGINGFACE_TOKEN} --add-to-git-credential HF_USER=$(huggingface-cli whoami | head -n 1) echo $HF_USER ``` record dataset ```bash python lerobot/scripts/control_robot.py record \ --robot-path lerobot/configs/robot/koch.yaml \ --fps 30 \ --root data \ --repo-id ${HF_USER}/koch_test \ --tags tutorial \ --num-episodes 2 \ --warmup-time-s 5 \ --episode-time-s 30 \ --reset-time-s 30 ``` full 50 episodes! ```bash python lerobot/scripts/control_robot.py record \ --robot-path lerobot/configs/robot/koch.yaml \ --fps 30 \ --root data \ --repo-id ${HF_USER}/koch_place_block \ --tags tutorial \ --num-episodes 50 \ --warmup-time-s 2 \ --episode-time-s 30 \ --reset-time-s 10 ``` Visualize ```bash python lerobot/scripts/visualize_dataset_html.py \ --root data \ --repo-id ${HF_USER}/koch_place_block ``` Replay ```bash python lerobot/scripts/control_robot.py replay \ --robot-path lerobot/configs/robot/koch.yaml \ --fps 30 \ --root data \ --repo-id ${HF_USER}/koch_place_block \ --episode 0 ``` Training!! ```bash DATA_DIR=data python lerobot/scripts/train.py \ dataset_repo_id=${HF_USER}/koch_place_block \ policy=act_koch_real \ env=koch_real \ hydra.run.dir=outputs/train/act_koch_place_block \ hydra.job.name=act_koch_place_block \ device=cuda \ wandb.enable=true ``` upload trained model {% code overflow="wrap" %} ```bash huggingface-cli upload ${HF_USER}/act_koch_place_block outputs/train/act_koch_place_block/checkpoints/last/pretrained_model ``` {% endcode %} eval ```bash python lerobot/scripts/control_robot.py record \ --robot-path lerobot/configs/robot/koch.yaml \ --fps 30 \ --root data \ --repo-id ${HF_USER}/eval_koch_place_block \ --tags tutorial eval \ --warmup-time-s 5 \ --episode-time-s 30 \ --reset-time-s 30 \ --num-episodes 10 \ -p outputs/train/act_koch_place_block/checkpoints/last/pretrained_model ``` Teleop Script ```python import tqdm from lerobot.common.robot_devices.motors.dynamixel import DynamixelMotorsBus from lerobot.common.robot_devices.motors.dynamixel import TorqueMode from lerobot.common.robot_devices.robots.manipulator import ManipulatorRobot from lerobot.common.robot_devices.cameras.opencv import OpenCVCamera leader_port = "/dev/ttyACM0" follower_port = "/dev/ttyACM1" leader_arm = DynamixelMotorsBus( port=leader_port, motors={ # name: (index, model) "shoulder_pan": (1, "xl330-m077"), "shoulder_lift": (2, "xl330-m077"), "elbow_flex": (3, "xl330-m077"), "wrist_flex": (4, "xl330-m077"), "wrist_roll": (5, "xl330-m077"), "gripper": (6, "xl330-m077"), }, ) follower_arm = DynamixelMotorsBus( port=follower_port, motors={ # name: (index, model) "shoulder_pan": (1, "xl430-w250"), "shoulder_lift": (2, "xl430-w250"), "elbow_flex": (3, "xl330-m288"), "wrist_flex": (4, "xl330-m288"), "wrist_roll": (5, "xl330-m288"), "gripper": (6, "xl330-m288"), }, ) robot = ManipulatorRobot( robot_type="koch", leader_arms={"main": leader_arm}, follower_arms={"main": follower_arm}, calibration_dir=".cache/calibration/koch", cameras={ "laptop": OpenCVCamera(0), }, ) robot.connect() follower_arm.write("Torque_Enable", TorqueMode.ENABLED.value) # # leader_pos = robot.leader_arms["main"].read("Present_Position") # # follower_pos = robot.follower_arms["main"].read("Present_Position") # # print(leader_pos) # # print(follower_pos) seconds = 120 frequency = 200 for _ in tqdm.tqdm(range(seconds*frequency)): leader_pos = robot.leader_arms["main"].read("Present_Position") robot.follower_arms["main"].write("Goal_Position", leader_pos) # observation, action = robot.teleop_step(record_data=True) # print(observation["observation.images.laptop"].shape) # print(observation["observation.images.phone"].shape) # print(observation["observation.images.laptop"].min().item()) # print(observation["observation.images.laptop"].max().item()) follower_arm.write("Torque_Enable", TorqueMode.DISABLED.value) robot.disconnect() ``` --- # Agent Instructions This documentation is published with GitBook. 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