Implementation of Trust Region Policy Optimization and Proximal Policy Optimization algorithms on the objective of Robot Walk.

RL Reach is a platform for running reproducible reinforcement learning experiments.

Pytorch implementations of various Deep Reinforcement Learning algorithms on pybullet environments.

This is a Biped simulated on pybullet physics engine, walking

ME 604- Robotics Project (IIT Bombay) Kuka Robot

Tutorial for Pybullet

This is a quadruped simulated on pybullet physics engine, walking using trot and bound mechanisms

HermiSim is a robotics simulation suite for loading URDF/XML files, rendering 3D environments, and running physics-based simulations with PyBullet. It features 3D visualization, sensor data simulation, and full control over simulations. Built with PyQt and modular in design, it’s ideal for robotics development and testing.

PyBullet keyboard shortcut/ hotkeys list

Explorer is a PyTorch reinforcement learning framework for exploring new ideas.

A training framework for Stable Baselines3 reinforcement learning agents, with hyperparameter optimization and pre-trained agents included.