Configuration Space Distance Fields for Manipulation Planning

Code release for ICLR 2023 paper "NTFields: Neural Time Fields for Physics-Informed Robot Motion Planning"

Deep Learning Visualization Toolkit（『飞桨』深度学习可视化工具 ）

CleanDiffuser: An Easy-to-use Modularized Library for Diffusion Models in Decision Making

Official repo for separable operator networks -- extreme-scale operator learning for parametric PDEs.

This repository includes the official implementation of our paper "Beyond Next-Token: Next-X Prediction for Autoregressive Visual Generation"

Quick and Self-Contained TensorRT Custom Plugin Implementation and Integration

一个功能强大的订阅链接转换工具，支持多种协议和输出格式。

An easy to use PyTorch to TensorRT converter

Project Page of Paper "Drive in Corridors: Enhancing the Safety of End-to-end Autonomous Driving via Corridor Learning and Planning"

[NeurIPS 2024] DeMo: Decoupling Motion Forecasting into Directional Intentions and Dynamic States

A curated list of world models for autonomous driving. Keep updated.

Code for the RA-L 2024 paper "Contingency Games for Multi-Agent Interactions."

Official Hardware Codebase for the Paper "BEHAVIOR Robot Suite: Streamlining Real-World Whole-Body Manipulation for Everyday Household Activities"

[IEEE RA-L'25] NavRL: Learning Safe Flight in Dynamic Environments (NVIDIA Isaac/Python/ROS1/ROS2)

[ICRA 2024] Differentiable Joint Conditional Prediction and Cost Evaluation for Tree Policy Planning

[NeurIPS 2024] SMART: Scalable Multi-agent Real-time Motion Generation via Next-token Prediction

很多镜像都在国外。比如 gcr 。国内下载很慢，需要加速。致力于提供连接全世界的稳定可靠安全的容器镜像服务。

[NeurIPS 2024] Behavioral Topology (BeTop), a multi-agent behavior formulation for interactive motion prediction and planning

A generative and self-guided robotic agent that endlessly propose and master new skills.

Code for the paper "Planning with Diffusion for Flexible Behavior Synthesis"

Physics-informed neural networks package

Solution for Waymo Motion Prediction Challenge 2022. Our implementation of MultiPath++

Paper reading notes on Deep Learning and Machine Learning

Fast Incremental Euclidean Distance Fields for Online Motion Planning of Aerial Robots

Code for TKDE paper "Self-supervised learning on graphs: Contrastive, generative, or predictive"

PyTorch Implementation of Physics-informed Neural Networks