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硬件清单

Google drive

Image Image Image Image

1: Dynamixel资料

技术文档

产品图纸

相关软件

配件选择

2: solidworks(2021)模型

Image Google drive

代码部分

1: 检查相机序号和配置文件是否对应

Image

python lerobot/common/robot_devices/cameras/opencv.py --fps 30 --record-time-s 3

2: 检查遥操臂的关节范围是否正常

Image

python lerobot/scripts/control_robot.py teleoperate --robot-path lerobot/configs/robot/gello_ur5.yaml

3: 遥操采集数据

python lerobot/scripts/control_robot.py record --robot-path lerobot/configs/robot/gello_ur5.yaml --repo-id cheney/dish --num-episodes 50

4: 可视化数据集

python lerobot/scripts/visualize_dataset_html.py   --root data   --repo-id cheney/dish

5: 训练模型

DATA_DIR=data python lerobot/scripts/train.py \
  dataset_repo_id={$HF_USER}/ur5_test\
  policy=act_ur5_real \
  env=ur5_real \
  hydra.run.dir=outputs/train/act_ur5_dish \
  hydra.job.name=act_ur5_dish \
  device=cuda \
  wandb.enable=true

6: 模型推理

python lerobot/scripts/control_robot.py record \
  --robot-path lerobot/configs/robot/gello_ur5.yaml \
  --fps 30 \
  --root data\
  --repo-id cheney/dish \
  --tags tutorial eval \
  --warmup-time-s 5 \
  --episode-time-s 30 \
  --reset-time-s 30 \
  --num-episodes 10 \
  -p outputs/train/act_ur5_dish/checkpoints/last/pretrained_model

7: 自定义评估（有需求可以自己实现）

python lerobot/scripts/control_robot.py eval \
  --robot-path lerobot/configs/robot/gello_ur5.yaml \
  -p outputs/train/act_ur5_dish/checkpoints/last/pretrained_model
python lerobot/common/robot_devices/cameras/opencv.py  --camera-config  lerobot/configs/robot/camera.yaml