Depth Anything 3

Lidar Localization and Mapping

Data preparation and loader for AMASS

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

Modular Reinforcement Learning (RL) library (implemented in PyTorch, JAX, and NVIDIA Warp) with support for Gymnasium/Gym, NVIDIA Isaac Lab, Brax and other environments

A Python framework for accelerated simulation, data generation and spatial computing.

Aerial Gym Simulator - Isaac Gym Simulator for Aerial Robots

Some Conferences' accepted paper lists (including AI, ML, Robotic)

Code for "Adversarial Motion Priors Make Good Substitutes for Complex Reward Functions"

深度学习经典、新论文逐段精读

A lightweight suite of motion imitation methods for training controllers.

An all-in-one and ready-to-use LiDAR-inertial odometry system for Livox LiDAR

A simple localization framework that can re-localize in built maps based on FAST-LIO.

A simple localization framework that can re-localize in one point-cloud map.

[IEEE RA-L] Air-IO: a learning-based IO framework targeted for UAV

🚀 AirVO upgrades to AirSLAM [TRO]🚀

ICRA2025 Paper List

ICRA2024 Paper List

Unofficial ICRA 2022 SLAM paper list

A fast and simple implementation of learning algorithms for robotics.

Paper Survey for Learning-based Odometry

Localization by LiDAR for Humanoid(like Unitree G1)

Reference PyTorch implementation and models for DINOv3

PyTorch code and models for the DINOv2 self-supervised learning method.

[CVPR 2025 Best Paper Award] VGGT: Visual Geometry Grounded Transformer

A Comprehensive Framework for Visual SLAM Systems and Datasets

This repository is used for automatic calibration between high resolution LiDAR and camera in targetless scenes.