Python sample codes and textbook for robotics algorithms.

A generative world for general-purpose robotics & embodied AI learning.

Common used path planning algorithms with animations.

Motion planning algorithms commonly used on autonomous vehicles. (path planning + path tracking)

Clean, Robust, and Unified PyTorch implementation of popular Deep Reinforcement Learning (DRL) algorithms (Q-learning, Duel DDQN, PER, C51, Noisy DQN, PPO, DDPG, TD3, SAC, ASL)

Isaac Gym Environments for Legged Robots

Fast and simple implementation of RL algorithms, designed to run fully on GPU.

Open-Source,ROS Robot Dog Kit

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…

[ICRA19] Crowd-aware Robot Navigation with Attention-based Deep Reinforcement Learning

ROS package for dynamic obstacle avoidance for ground robots trained with deep RL

Motion planning and Navigation of AGV/AMR：python implementation of Dijkstra, A*, JPS, D*, LPA*, D* Lite, (Lazy)Theta*, RRT, RRT*, RRT-Connect, Informed RRT*, ACO, Voronoi, PID, DWA, APF, LQR, MPC, …

Elevation Mapping on GPU.

[CVPR 2025] Truncated Diffusion Model for Real-Time End-to-End Autonomous Driving

This is a project about deep reinforcement learning autonomous obstacle avoidance algorithm for UAV.

Aerial Gym Simulator - Isaac Gym Simulator for Aerial Robots

ViPlanner: Visual Semantic Imperative Learning for Local Navigation

Learning-based locomotion control from OpenRobotLab, including Hybrid Internal Model & H-Infinity Locomotion Control

Implementation of the paper "Towards Optimally Decentralized Multi-Robot Collision Avoidance via Deep Reinforcement Learning"

Simulations for TurtleBot3

RL Extension Library for Robots, Based on IsaacLab.

Learn Robotics with JdeRobot

Reinforcement learning algorithms implemented for Tensorflow 2.0+ [DQN, DDPG, AE-DDPG, SAC, PPO, Primal-Dual DDPG]

DSAC-v2; DSAC-T; DASC; Distributional Soft Actor-Critic

PyTorch implementation of Soft-Actor-Critic and Prioritized Experience Replay (PER) + Emphasizing Recent Experience (ERE) + Munchausen RL + D2RL and parallel Environments.

ROS driver for controlling Boston Dynamics' Spot robot

iPlanner: Imperative Path Planning. An end-to-end learning planning framework using a novel unsupervised imperative learning approach

Toolkit for vision-guided quadrupedal locomotion research