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Beihang University& Institute of Physics, CAS
- Beijing
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18:32
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Implementation of Recovery RL: Safe Reinforcement Learning With Learned Recovery Zones.
An agentic skills framework & software development methodology that works.
RoboVerse: Towards a Unified Platform, Dataset and Benchmark for Scalable and Generalizable Robot Learning
code for adjoint-based diffusion samplers
Pytorch Implementation (unofficial) of the paper "Mean Flows for One-step Generative Modeling" by Geng et al.
Official implementation for DSRL, Steering Your Diffusion Policy with Latent Space Reinforcement Learning (CoRL 2025)
[ICLR 2026 Oral] DiffusionNFT: Online Diffusion Reinforcement with Forward Process
Hand-eye calibration integration using aruco_ros and VISP
This repository presents a comprehensive solution to the hand-eye calibration problem, a fundamental challenge in robotics and computer vision. Hand-eye calibration is critical for applications req…
Python tools to perform time-synchronization and hand-eye calibration.
Calibrate the camera with ZhangZhengyou method (in both distortion case and no distortion case)
Deep Learning for Camera Calibration and Beyond: A Survey
Basic Python interface for MoveIt 2 built on top of ROS 2 actions and services
[ICML 2025] The official implementation of the paper "On the Guidance of Flow Matching"
Official repo for GraspGen: A Diffusion-based Framework for 6-DOF Grasping
Official codes for the paper "GARDO: Reinforcing Diffusion Models without Reward Hacking"
Baseline model for "GraspNet-1Billion: A Large-Scale Benchmark for General Object Grasping" (CVPR 2020)
Official implementation of Diffusion Policy Policy Optimization, arxiv 2024
Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.
Official implementation of "Flow Based Policy for Online Reinforcement Learning"
This repository contains code for the paper "Why Diffusion Models Don't Memorize: The Role of Implicit Dynamical Regularization in Training" by T. Bonnaire, R. Urfin, G. Biroli and M. Mézard.
A curated list of Diffusion Model in RL resources (continually updated)

