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

Low-level locomotion policy training in Isaac Lab

Repository relating to "Contrastive Initial State Buffer for Reinforcement Learning" (ICRA, 2024).

Code for SDS: Quadrupedal Skill Synthesis from Single Video Demonstration

Source code for the paper DiffuseLoco: Real-Time Legged Locomotion Control with Diffusion from Offline Datasets

Learning Quadrotor Control From Visual Features Using Differentiable Simulation

Wheel-legged robot simulation files.

Reproduce of MPC-D-CBF

Aerial Gym Simulator - Isaac Gym Simulator for Aerial Robots

A python based light weight robot simulator for the intelligent robotics navigation and learning

Use ros_control to realize sim2sim and sim2real.

two wheel legged bot for Isaac gym reinforcement learning

Simulation verification and physical deployment of robot reinforcement learning algorithms, suitable for quadruped robots, wheeled robots, and humanoid robots. "sar" represents "simulation and real"

unitree Go2 robot learns locomotion with N-P3O algorithm and HIM alike policy trained by isaacgym

A generic robot RL library based on IsaacLab

Open source materials for a novel structured legged robot, including mechanical design, electronic design, algorithm simulation, and software development. | 一个新型结构的轮腿机器人开源资料，包含机械设计、电子设计、算法仿真、软件开发等材料

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

全球最小的桌面级双轮腿机器人！

Create pgm map from Gazebo world file for ROS localization. Tested on Ubuntu 20.04, ROS Noetic, Boost 1.71，Gazebo 11

An obstacle tracking ROS package for detecting obstacles using 2D LiDAR scan using an Extended object tracking algorithm

A ROS package for 2D obstacle detection based on laser range data.

The ros package of rvo library

Reinforcement Learning (RL) based navigation implementation for mobile robot navigation. The algorithms of TD3, DDPG, SAC, DQN, Q-Learning, and SARSA were implemented.

Synthesizing action selection policies from noisy, low-level demonstrations