Unitree Go2, Unitree G1 support for Nvidia Isaac Lab (Isaac Gym / Isaac Sim)
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Updated
May 28, 2025 - Python
Unitree Go2, Unitree G1 support for Nvidia Isaac Lab (Isaac Gym / Isaac Sim)
Codebase for Kinova Gen3 training in Isaac Lab, sim2real transfer and ROS deployment.
Isaaclab-based grasp learning test bench
Multiple experimental environments for Isaac Lab.
RL for Walk and Stop for quadruped legged robot (AlienGo - Unitree) + Examples. PPO (SKRL), DDPG (SKRL, SB3), TD3 (SB3).
Simulation Code for RobRAN, A Unified Robotics Framework for Reinforcement Learning-Based Autonomous Navigation.
Reinforcement learning pipeline for specific configured robot to learn to reach randomly sampled target poses within its workspace.
decouped imitation for whole-body humanoid natural locomotion
Biped robot locomotion with deep RL: Isaac Lab + MuJoCo, custom PPO/SAC/DDPG/D4PG/MPO, MLP/LSTM/Transformer, motion imitation, sim-to-real
Low Level RL Controller for G1
VLM-RL Hierarchical Loco-Manupilation For Long-Horizon Tasks With G1 robot in Isaac Lab/Sim
NavBot-X Isaac Lab is a premium robotics simulation project focused on building an autonomous inspection rover in Isaac Sim / Isaac Lab. It brings together cinematic environment design, checkpoint-based task logic, omnidirectional rover control concepts, and gesture-control integration, with future expansion toward RL and Physical AI
This repository contains the implementation, data-generation pipelines, and trained behavior-cloning models for a kitchen pick-and-place task using IsaacLab. Task: a Franka Emika manipulator picks a tomato soup can (container) from inside a fridge and places it inside the microwave cavity.
This project investigates the robustness of humanoid locomotion policies trained with imitation learning and reinforcement learning in simulation. The primary research question is: how does a learned PPO controller respond to partial actuator or degree-of-freedom failure, and which joints are most critical for maintaining stable locomotion?
A legged locomotion project
Z.O.E. Hexapod: 18-DOF gait discovery in Isaac Lab 4.5. Tuned for ST3215 servos, it uses Pytorch PPO to bridge the Sim-to-Real gap on rough terrain.
A framework built on NVIDIA Isaac Sim for the implementation of evaluations and benchmarking of imitation learning algorithms for robotic manipulation.
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