- shanghai
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19:24
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Stars
Fork of mjlab which supports unitree H1 & robotiq_2f85, personal implementation of the locomotion policy training in "HOMIE: Humanoid Loco-Manipulation with Isomorphic Exoskeleton Cockpit [RSS2025]"
Official implementation of Click-and-Traverse
Official implementation for DSRL, Steering Your Diffusion Policy with Latent Space Reinforcement Learning (CoRL 2025)
Lightweight implementation of Robotic World Model (RWM) and Uncertainty-Aware Robotic World Model (RWM-U)
Physically-Plausible Image Signal Processing (PPISP) for Radiance Field Reconstruction
[ICLR 2026] π^3: Permutation-Equivariant Visual Geometry Learning
Running VLA at 30Hz frame rate and 480Hz trajectory frequency
[RA-L 26] Learning on the Fly: Rapid Policy Adaptation via Differentiable Simulation
Optimizing diffusion for production-ready speeds
Extend the navigation capabilities of Anymal-C in IsaacLab using Deep Reinforcement Learning
[ASPLOS 2026] CLM: Removing the GPU Memory Barrier for 3D Gaussian Splatting with CPU Offloading
Muskie: Multi-view Masked Image Modeling for 3D Vision Pre-training
Pixio: a capable vision encoder dedicated to dense prediction, simply by pixel reconstruction
Official implementation of "Learning Diverse Natural Behaviors for Enhancing the Agility of Quadrupedal Robots"
A place to store reusable transformer components of my own creation or found on the interwebs
Autonomous Navigation and Collision Avoidance for Ground Robots
MATRiX is an advanced simulation platform that integrates MuJoCo, Unreal Engine 5, and CARLA to provide high-fidelity, interactive environments for robotics research.
Voice Activity Detector (VAD) : low-latency, high-performance and lightweight
Rover and space-related reinforcement learning environments implemented for Isaac Sim and Isaac Lab.
All-in-one training for vision models (YOLO, ViTs, RT-DETR, DINOv3): pretraining, fine-tuning, distillation.
Atom3d, atomising geometry, is a mesh processing toolbox specifically designed for 3D learning.
train, export, and deploy HimLoco policies in the Isaac Lab environment
This repository provides a set of reinforcement learning tasks for Booster robots using Isaac Lab.


