Mingrui YU

Mingrui YU

A robotics learner

Mingrui YU / 于铭瑞 / Harry YU

I am Mingrui YU, a robotics learner. I’m now pursuing the Ph.D. degree in the Intelligent Manipulation Lab, Department of Automation, Tsinghua University, under the supervision of Prof. Xiang Li. From 10/2023 to 03/2024, I was a visiting student at the MSC Lab in UC Berkeley, under the supervision of Prof. Masayoshi Tomizuka.

I’m interested in machine learning, planning, and control with their applications to robotic dexterous manipulation of various objects, including in-hand manipulation and deformable object manipulation.

I am leading an NSFC Youth Student Research Project (for PhD students) / 首批国家自然科学基金青年学生基础研究项目（博士生项目）entitled “Visual-tactile dexterous manipulation of deformable linear objects with a dual-arm robot”.

Email: mingruiyu98@gmail.com (recommended); ymr20@mails.tsinghua.edu.cn (国内使用).

Education

Department of Automation, Tsinghua University (Beijing, China)   08/2020 - present
Ph.D. student in Control Science and Engineering
GPA: 3.95/4.0

Department of Automation, Xi’an Jiaotong University (Xi’an, China)   08/2016 - 07/2020
B.Eng. in Automation (Honors Engineering Program, 钱学森班)
GPA: 4.09/4.3, Ranking: 1/35

Research Experience

Robotics X, Tencent (Shenzhen, China)   06/2024 - 09/2024
Advisor: Dr. Yu Zheng
Topic: Dexterous grasping and manipulation

Mechanical Systems Control Lab, University of California, Berkeley   10/2023 - 03/2024
Advisor: Prof. Masayoshi Tomizuka
Topic: Dexterous manipulation of (deformable) objects

Institute of Automation, Chinese Academy of Sciences (Beijing, China)   07/2018 - 06/2019
Advisor: Prof. Yisheng Lv
Topic: Reinforment learning for intelligent transportation system

Publications

Journal Papers

  1. M. Yu, K. Lv, C. Wang, Y. Jiang, M. Tomizuka, and X. Li, “Generalizable whole-body global manipulation of deformable linear objects by dual-arm robot in 3-D constrained environments”, The International Journal of Robotics Research, 2024. [Paper] [Website]
  2. M. Yu, K. Lv, H. Zhong, S. Song, and X. Li, “Global Model Learning for Large Deformation Control of Elastic Deformable Linear Objects: An Efficient and Adaptive Approach,” IEEE Transactions on Robotics, 2022. [Paper] [Website]
  3. 于铭瑞, 李翔, “面向线状柔性物体的机器人操作研究进展与展望”, 机器人, 2024.

Conference Papers

  1. M. Yu, B. Liang, X. Zhang, X. Zhu, L. Sun, C. Wang, X. Li, M. Tomizuka, “In-Hand Following of Deformable Linear Objects Using Dexterous Fingers With Tactile Sensing”, 2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2024. (Oral, Top 12%) [Paper] [Website]
  2. Y. Jiang, M. Yu , X. Zhu, M. Tomizuka, X. Li, “Contact-Implicit Model Predictive Control for Dexterous In-hand Manipulation: A Long-Horizon and Robust Approach”, 2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2024. [Paper] [Website]
  3. X. Yan, S. Luo, Y. Jiang, M. Yu, C. Chen, G. Huang, X. Li, “A Unified Interaction Control Framework for Safe Robotic Ultrasound Scanning with Human-Intention-Aware Compliance”, 2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2024. (Oral, Top 12%)
  4. M. Yu, K. Lv, C. Wang, M. Tomizuka, and X. Li, “A Coarse-to-Fine Framework for Dual-Arm Manipulation of Deformable Linear Objects with Whole-Body Obstacle Avoidance”, 2023 IEEE International Conference on Robotics and Automation (ICRA), 2023. (Best Paper Award at the ICRA 2023 Workshop on Representing and Manipulating Deformable Objects) [Paper] [Website]
  5. K. Lv, M. Yu, Y. Pu, and X. Li, “Learning to Estimate 3-D states of Deformable Linear Objects from Single-Frame Occluded Point Clouds”, 2023 IEEE International Conference on Robotics and Automation (ICRA), 2023. [Paper] [Video]
  6. M. Yu, H. Zhong, and X. Li, “Shape Control of Deformable Linear Objects with Offline and Online Learning of Local Linear Deformation Models,” 2022 IEEE International Conference on Robotics and Automation (ICRA), 2022. [Paper] [Website]
  7. 于铭瑞, 贾永奕, 李翔, “高危化工机器人研究与应用综述”, 2021 中国自动化大会 (CAC), 2021. [Paper]
  8. H. Zhong, Z. Xu, G. Ma, M. Yu, and X. Li, “Regressor-Based Model Adaptation for Shaping Deformable Linear Objects with Force Control,” 2023 IEEE Interational Conference on Robotics and Biomimetics (ROBIO), 2023. [Paper]
  9. F. Xiong, Y. Ding, M. Yu, W. Zhao, N. Zheng, P. Ren, “A lightweight sequence-based unsupervised loop closure detection,” 2021 International Joint Conference on Neural Networks (IJCNN), 2021. [Paper]
  10. M. Yu, J. Chai, Y. Lv and G. Xiong, “An effective deep reinforcement learning approach for adaptive traffic signal control,” 2020 Chinese Automation Congress (CAC), 2020. [Paper]

Patents

  1. 吕宜生, 柴嘉骏, 于铭瑞, 陈圆圆, 熊刚, 朱凤华, 王飞跃. 基于深度强化学习单路口交通信号控制方法、系统、装置. 申请号：2019106294891, 申请日：2019.07.12. 授权公告号：CN110428615B，授权公告日：2021.06.22.

  2. 孙宏滨, 南智雄, 于铭瑞,  魏平, 徐林海, 郑南宁. 一种车辆的车道保持控制方法. 申请号：2018100047576, 申请日：2018.01.03. 授权公告号：CN108297866B, 授权公告日：2019.10.15.

Competitions

Awards & Honors

Projects

Project Page

Academic Service