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A GPU-Accelerated Differentiable Simulation Framework for Efficient Quadrotor Policy Learning
Jax Official Implementation of T-RO Paper: Songyuan Zhang*, Oswin So*, Kunal Garg, Chuchu Fan: "GCBF+: A Neural Graph Control Barrier Function Framework for Distributed Safe Multi-Agent Control".
A generic sampling-based MPC python library based on jax
Published on Nature Machine Intelligence! The first real robot(quadrotor) based on differentiable physics training.
Multi-objective Gymnasium environments for reinforcement learning
Multi-Objective Reinforcement Learning algorithms implementations.
Official Implementation of RSS2025 Paper: Songyuan Zhang*, Oswin So*, Mitchell Black, Zachary Serlin, Chuchu Fan: "Solving Multi-Agent Safe Optimal Control with Distributed Epigraph Form MARL".
A ROS implementation of ORB_SLAM2
Public code for "Data-Efficient Decentralized Visual SLAM"
Code release for "A Testbed for Multi-Drone Volleyball Game Combining Motion Control and Strategic Play" (NeurIPS 2025), https://arxiv.org/abs/2502.01932
Simulation and analysis tools for autonomous F-16 maneuvers as a V&V benchmark
Python Version of F-16 Maneuver Verification Benchmark
Online Goal-Conditioned Reinforcement Learning in JAX. ICLR 2025 Spotlight.
Python tool for converting files and office documents to Markdown.
Massively parallel rigidbody physics simulation on accelerator hardware.