Roboschool is a set of open source robot simulation environments for reinforcement learning, created as an alternative to the Mujoco physics engine. It integrates with OpenAI Gym and provides a variety of continuous control tasks, including humanoid locomotion, quadrupeds, and robotic arms. The library is built on the Bullet Physics engine, making it accessible without the licensing requirements of Mujoco. Roboschool includes training scripts and examples for applying reinforcement learning algorithms to its environments. While the project has since been deprecated in favor of more modern frameworks, it remains historically significant as a bridge between early reinforcement learning research and scalable, open-access environments. Its goal was to make reproducible robot learning experiments available to a wider audience without restrictive dependencies .
Features
- Physics-based robotics environments built on Bullet Physics
- Seamless integration with OpenAI Gym API
- Continuous control tasks such as humanoid and quadruped locomotion
- Example training scripts for reinforcement learning agents
- Open alternative to Mujoco with no licensing restrictions
- Supports visualization for debugging and research demonstrations