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How to Run the Code

Create a conda environment using environment.yml which will automatically install all required dependencies. (Note: Use Anaconda preferably)

conda env create -f environment.yml
pip install git+https://github.com/ElyasYassin/AlBornoLab-myosuite.git
pip install git+https://github.com/ElyasYassin/mjrl-modified.git
(or use the Anaconda GUI to import environment)

If environment.yml doesn't work for whatever reason you can:

conda env create -n myosuite
conda install python=3.8.18
pip install -r requirement

Walkthrough

  1. Train the policy using either mjrl training (MuJoCo Reinforcement Learning module) or sb3 training (Stable Baselines 3 module).
  2. After training is done, verify the visual outcome using load policy.

Miscellaneous

  • Inverse Dynamics: Reproduce a movement from a CSV file that stores the intensity of each muscle actuator as a function of time.
  • Testing Models: Use this to see the composition of models, primarily how many joints and muscles the model has.

About

Using MuJoCo and Myosuite to create a center reach out task

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