Reinforcement learning with musculoskeletal models in OpenSim

NeurIPS 2019: Learn to Move - Walk Around

Design artificial intelligent controllers for the human body to accomplish diverse locomotion tasks. Participate in the NeurIPS 2019 challenge to win prizes and fame.

Learn more about the challenge →

OpenSim RL

Use our musculoskeletal reinforcement learning environment for other projects in computer science, neuroscience, biomechanics, etc.

Learn more about osim-rl →

Get up and running in seconds.

Quick-start Instructions

~ $ conda create -n opensim-rl -c kidzik opensim python=3.6.1

~ $ source activate opensim-rl

~(opensim-rl) $ conda install -c conda-forge lapack git

~(opensim-rl) $ pip install git+

~(opensim-rl) $ python

from osim.env import ProstheticsEnv
env = ProstheticsEnv(visualize=True)
observation = env.reset()
for i in range(200):
    o, r, d, i = env.step(env.action_space.sample())

NIPS 2017: Learning to Run challenge

In 2017 we used osim-rl in a challenge at NIPS were participants were asked to build controllers for running. They did great :)