osim-rl package allows you to synthesize physiologically accurate movement by combining biomechanical expertise embeded in OpenSim simulation software with state-of-the-art control strategies using Deep Reinforcement Learning.
Our objectives are to:
- use Reinforcement Learning (RL) to solve problems in healthcare,
- promote open-source tools in RL research (the physics simulator, the RL environment, and the competition platform on which we run challenges are all open-source),
- encourage RL research in computationally complex environments, with stochasticity and highly-dimensional action spaces, relevant to real-life applications,
- bridge biomechanics, neuroscience, and computer science communities.