Stars
Pytorch version of the MPC in model-based reinforcement learning (MBRL), currently only test in the CartPole-swing-up environment
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 reinforcem…
This is a project about robotic manipulation motion planning using deep reinforcement learning based on ROS and Gazebo simulation
End to end motion planner using Deep Deterministic Policy Gradient (DDPG) in gazebo
Deep Reinforcement Learning for mobile robot navigation in ROS Gazebo simulator. Using Twin Delayed Deep Deterministic Policy Gradient (TD3) neural network, a robot learns to navigate to a random g…
Implementation of the paper "Towards Optimally Decentralized Multi-Robot Collision Avoidance via Deep Reinforcement Learning"
Reinforcement learning using rlkit, UR5, Robotiq gripper on ROS(Robot Operating System)
Reinforcement Learning framework for Robotics
Training a humanoid robot for locomotion using Reinforcement Learning
roposes an efficient grasp-to-place strategy for robotic manipulation in sparse environments using a deep Q-network. Requires less computation and time, generalizes well across scenarios, and achie…
Leveraging Large Language Models for Visual Target Navigation
Concise pytorch implements of DRL algorithms, including REINFORCE, A2C, DQN, PPO(discrete and continuous), DDPG, TD3, SAC.
PyTorch implementation of DQN, AC, ACER, A2C, A3C, PG, DDPG, TRPO, PPO, SAC, TD3 and ....