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Imitation learning algorithms with Co-training for Mobile ALOHA: ACT, Diffusion Policy, VINN

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Imitation Learning Algorithms and Co-training for Mobile ALOHA

Original Project Websites:

This repo contains the implementation of ACT, Diffusion Policy, and VINN. To work with real hardware, you would need to install ALOHA.

Repo Structure

  • act_plus_plus
    • act_plus_plus
      • detr Model definitions of ACT, modified from DETR
      • constants.py Constants shared across files
      • policy.py An adaptor for ACT policy
      • utils.py Utils such as data loading and helper functions
      • scripts
        • imitate_episodes.py Train and Evaluate ACT
        • visualize_episodes.py Save videos from a .hdf5 dataset

Installation

There are two recommended ways to install ACT: using conda or venv. Using venv is preferred due its ease of use against frameworks like ROS.

Installation Using venv

sudo apt-get install python3-venv
python3 -m venv ~/act # creates a venv "act" in the home directory, can be created anywhere
source ~/act/bin/activate
pip install dm_control==1.0.14
pip install einops
pip install h5py
pip install ipython
pip install matplotlib
pip install modern_robotics
pip install mujoco==2.3.7
pip install opencv-python
pip install packaging
pip install pexpect
pip install pyquaternion
pip install pyyaml
pip install rospkg
pip install torch
pip install torchvision
pip install transforms3d
pip install wandb

The r2d2 branch of robomimic must also be installed.

git clone -b r2d2 https://github.com/ARISE-Initiative/robomimic.git
cd robomimic
pip install -e .

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