A comprehensive framework for reinforcement learning in robotics, which allows users to train their robots in both simulated and real-world environments.

MultiROS is an open-source ROS based simulation environment designed for concurrent deep reinforcement learning. It provides a flexible and scalable framework for training and evaluating reinforcement learning agents for complex robotic tasks.

RealROS is an open-source Python framework that seamlessly integrates with ROS (Robot Operating System) to create real-world robotics environments tailored for reinforcement learning (RL) applications. This modular framework simplifies RL development, enabling real-time training with physical robots

Goal-conditioned reinforcement learning like 🔥

Reinforcement Learning for Unmanned Airial Vehicles

Farama Gymnasium API Wrapper for the DeepMind Control Suite and DeepMind Robot Manipulation Tasks