ACT (Action Chunking Transformer)¶

1. Install¶

pip install pyquaternion pyyaml rospkg pexpect mujoco==2.3.7 dm_control==1.0.14 opencv-python matplotlib einops packaging h5py ipython

cd adetr && pip install -e .

2. Prepare Training Data¶

This step performs data preprocessing, converting the original RoboTwin 2.0 data into the format required for ACT training. The expert_data_num parameter specifies the number of trajectory pairs to be used as training data.

bash process_data.sh ${task_name} ${task_config} ${expert_data_num}

3. Train Policy¶

This step launches the training process. By default, the model is trained for 6,000 steps.

bash train.sh ${task_name} ${task_config} ${expert_data_num} ${seed} ${gpu_id}

4. Eval Policy¶

The task_config field refers to the evaluation environment configuration, while the ckpt_setting field refers to the training data configuration used during policy learning.

bash eval.sh ${task_name} ${task_config} ${ckpt_setting} ${expert_data_num} ${seed} ${gpu_id}

The evaluation results, including videos, will be saved in the eval_result directory under the project root.