Mingdong Wu | 吴铭东

2025

1. IROS 2025

   SimLauncher: Launching Sample-Efficient Real-world Robotic Reinforcement Learning via Simulation Pre-training

   Mingdong Wu*, Lehong Wu*, Yizhuo Wu*, Weiyao Huang, Hongwei Fan, Zheyuan Hu, Haoran Geng, Jinzhou Li, Jiahe Ying, Long Yang, and  others

   IEEE/RSJ International Conference on Intelligent Robots and Systems, 2025

   Bib PDF Video

   @article{wu2025simlauncher,
     video = {https://www.dropbox.com/scl/fi/5yif7dl2bz4pcv2uw9s03/Training-Timelapse.mp4?rlkey=iga15684bqfy2fz9fwk6edsay&st=mryoerqt&dl=0},
     title = {SimLauncher: Launching Sample-Efficient Real-world Robotic Reinforcement Learning via Simulation Pre-training},
     author = {Wu*, Mingdong and Wu*, Lehong and Wu*, Yizhuo and Huang, Weiyao and Fan, Hongwei and Hu, Zheyuan and Geng, Haoran and Li, Jinzhou and Ying, Jiahe and Yang, Long and others},
     journal = {IEEE/RSJ International Conference on Intelligent Robots and Systems},
     year = {2025}
   }

   
2. CoRL 2025

   UniTac2Pose: A Unified Approach Learned in Simulation for Generalizable Visuotactile In-hand Pose Estimation

   Mingdong Wu*, Long Yan*, Jin Liu*, Weiyao Huang, Lehong Wu, Zelin Chen, Daolin Ma, and Hao Dong

   Conference on Robot Learning, 2025

   Bib PDFCode

   @article{wu2025unitac2pose,
     title = {UniTac2Pose: A Unified Approach Learned in Simulation for Generalizable Visuotactile In-hand Pose Estimation},
     author = {Wu*, Mingdong and Yan*, Long and Liu*, Jin and Huang, Weiyao and Wu, Lehong and Chen, Zelin and Ma, Daolin and Dong, Hao},
     journal = {Conference on Robot Learning},
     year = {2025}
   }

   
3. IROS 2025

   Adaptive Visuo-Tactile Fusion with Predictive Force Attention for Dexterous Manipulation

   Jinzhou Li*, Tianhao Wu*, Jiyao Zhang, Zeyuan Chen, Haotian Jin, Mingdong Wu, Yujun Shen, Yaodong Yang, and Hao Dong

   IEEE/RSJ International Conference on Intelligent Robots and Systems, 2025

   Bib PDF

   @article{li2025adaptive,
     title = {Adaptive Visuo-Tactile Fusion with Predictive Force Attention for Dexterous Manipulation},
     author = {Li*, Jinzhou and Wu*, Tianhao and Zhang, Jiyao and Chen, Zeyuan and Jin, Haotian and Wu, Mingdong and Shen, Yujun and Yang, Yaodong and Dong, Hao},
     journal = {IEEE/RSJ International Conference on Intelligent Robots and Systems},
     year = {2025}
   }

   
4. ICRA 2025

   Canonical representation and force-based pretraining of 3d tactile for dexterous visuo-tactile policy learning

   Tianhao Wu, Jinzhou Li*, Jiyao Zhang*, Mingdong Wu, and Hao Dong

   IEEE International Conference on Robotics and Automation, 2025

   Bib PDF

   @article{wu2024canonical,
     title = {Canonical representation and force-based pretraining of 3d tactile for dexterous visuo-tactile policy learning},
     author = {Wu, Tianhao and Li*, Jinzhou and Zhang*, Jiyao and Wu, Mingdong and Dong, Hao},
     journal = {IEEE International Conference on Robotics and Automation},
     year = {2025}
   }

   

2024

1. ECCV 2024

   Omni6DPose: A Benchmark and Model for Universal 6D Object Pose Estimation and Tracking

   Jiyao Zhang*, Weiyao Huang*, Bo Peng*, Mingdong Wu, Fei Hu, Zijian Chen, Bo Zhao, and Hao Dong

   European Conference on Computer Vision, 2024

   Bib PDF Website

   @article{zhang2024omni6dpose,
     title = {Omni6DPose: A Benchmark and Model for Universal 6D Object Pose Estimation and Tracking},
     author = {Zhang*, Jiyao and Huang*, Weiyao and Peng*, Bo and Wu, Mingdong and Hu, Fei and Chen, Zijian and Zhao, Bo and Dong, Hao},
     journal = {European Conference on Computer Vision},
     year = {2024}
   }

   
2. RAL 2024

   Distilling Functional Rearrangement Priors from Large Models

   Yiming Zeng*, Mingdong Wu*, Long Yang, Jiyao Zhang, Hao Ding, Hui Cheng, and Hao Dong

   IEEE Robotics and Automation Letters, 2024

   Bib PDF Website

   @article{zeng2023distilling,
     title = {Distilling Functional Rearrangement Priors from Large Models},
     author = {Zeng*, Yiming and Wu*, Mingdong and Yang, Long and Zhang, Jiyao and Ding, Hao and Cheng, Hui and Dong, Hao},
     journal = {IEEE Robotics and Automation Letters},
     year = {2024}
   }

   

2023

1. NeurIPS 2023

   GenPose: Generative Category-level Object Pose Estimation via Diffusion Models

   Jiyao Zhang*, Mingdong Wu*, and Hao Dong

   Thirty-seventh Conference on Neural Information Processing Systems, 2023

   Abs Bib PDF Website Code 机器之心

   We explore a pure generative approach to tackle the multi-hypothesis issue in 6D Category-level Object Pose Estimation. The key idea is to generate pose candidates using a score-based diffusion model and filter out outliers using an energy-based diffusion model. By aggregating the remaining candidates, we can obtain a robust and high-quality output pose.

   @article{zhang2023genpose,
     news = {机器之心},
     news_link = {https://mp.weixin.qq.com/s/RYV_aap9eYtwX_4_Ghr5Vw},
     sota_link = {https://paperswithcode.com/sota/6d-pose-estimation-using-rgbd-on-real275?p=genpose-generative-category-level-object-pose},
     sota_badge = {https://img.shields.io/endpoint.svg?url=https://paperswithcode.com/badge/genpose-generative-category-level-object-pose/6d-pose-estimation-using-rgbd-on-real275},
     star = {https://img.shields.io/github/stars/Jiyao06/GenPose?style=social&label=Code+Stars},
     title = {GenPose: Generative Category-level Object Pose Estimation via Diffusion Models},
     author = {Zhang*, Jiyao and Wu*, Mingdong and Dong, Hao},
     journal = {Thirty-seventh Conference on Neural Information Processing Systems},
     year = {2023}
   }

   
2. NeurIPS 2023

   Learning Score-based Grasping Primitive for Human-assisting Dexterous Grasping

   Tianhao Wu*, Mingdong Wu*, Jiyao Zhang, Yunchong Gan, and Hao Dong

   Thirty-seventh Conference on Neural Information Processing Systems, 2023

   Bib PDF Website Code 新智元

   @article{wu2023learning,
     news = {新智元},
     news_link = {https://mp.weixin.qq.com/s/hpzZWMizR8tPSGIvGVjPoA},
     star = {https://img.shields.io/github/stars/tianhaowuhz/human-assisting-dex-grasp?style=social&label=Code+Stars},
     title = {Learning Score-based Grasping Primitive for Human-assisting Dexterous Grasping},
     author = {Wu*, Tianhao and Wu*, Mingdong and Zhang, Jiyao and Gan, Yunchong and Dong, Hao},
     journal = {Thirty-seventh Conference on Neural Information Processing Systems},
     year = {2023}
   }

   

2022

1. NeurIPS 2022

   TarGF: Learning Target Gradient Field to Rearrange Objects without Explicit Goal Specification

   Mingdong Wu*, Fangwei Zhong*, Yulong Xia, and Hao Dong

   Advances in Neural Information Processing Systems, 2022

   Abs Bib PDF WebsiteCode

   We study object rearrangement without explicit goal specification. The agent is given examples from a target distribution and aims at rearranging objects to increase the likelihood of the distribution. Our key idea is to learn a target gradient field that indicates the fastest direction to increase the likelihood from examples via score-matching.

   @inproceedings{wu2022targf,
     title = {Tar{GF}: Learning Target Gradient Field to Rearrange Objects without Explicit Goal Specification},
     author = {Wu*, Mingdong and Zhong*, Fangwei and Xia, Yulong and Dong, Hao},
     booktitle = {Advances in Neural Information Processing Systems},
     editor = {Oh, Alice H. and Agarwal, Alekh and Belgrave, Danielle and Cho, Kyunghyun},
     year = {2022},
     url = {https://openreview.net/forum?id=Euv1nXN98P3}
   }