关于 | Li Mingyu 李明宇

机械工程与机器人学院

同济大学

中国上海

我是同济大学机械工程与机器人学院的一名大三本科生，研究方向为机械电子与机器视觉，聚焦机器人抓取与嵌入式视觉系统。

本人GPA 4.28/5.0，CET-6 510分，核心专业课成绩优异。曾获同济大学校奖学金一等奖及校级优秀学生荣誉（2025年）。具备扎实的机械、编程与算法基础，主攻智能机器人、机器视觉交叉方向。

科研上，我聚焦机器人抓取与嵌入式视觉，主持灵巧手零样本视觉抓取项目，参与机械臂嵌入式控制、智能制造仿真课题；以一作兼通讯作者 IEEE ICARM 2026 会议论文已录用，并有一项实用新型专利申请获国家知识产权局受理。

在校期间深耕课题组前沿研讨，获多项国家级竞赛奖项，工程实践与协作能力扎实。

同济大学校级优秀学生 / Tongji University Outstanding Student Award

动态

May 16, 2026	Won Shanghai Regional First Prize and National Final Qualification in 15th Shanghai College Student Mechanical Engineering Innovation Competition & 12th National College Student Mechanical Design Innovation Competition Shanghai Regional (Smart Shrimp Peeling / 智械解虾)
Apr 03, 2026	Submitted a first-author and corresponding-author paper to IEEE ICARM 2026: “Hardware-Software Co-Design of a Dual-Vision, Infinite-Roll Hand for Edge-Native Grasping.”
Aug 23, 2025	Won National Third Prize in BMHRI Cup Logistics Technology Creativity Contest
Jul 23, 2025	Won Regional Second Prize in 20th National University Students Intelligent Car Race - Baidu Smart Transportation Track
Jul 07, 2025	Won National First Prize in Higher Education Cup National College Student Advanced Graphics Technology and Product Information Modeling Innovation Competition - Additive Manufacturing Track
Jun 10, 2025	Utility model patent application “Folding Cane Chair” accepted by the China National Intellectual Property Administration. Application No. 202521174680.9.
May 16, 2025	Won Municipal First Prize in 14th Shanghai College Student Mechanical Engineering Innovation Competition

代表论文

ICARM
Hardware-Software Co-Design of a Dual-Vision, Infinite-Roll Hand for Edge-Native Grasping

Mingyu Li, Zhixian Gao, and Zhangchi Guo

In Proceedings of the IEEE International Conference on Advanced Robotics and Mechatronics (ICARM), Paris, France, Tongji University , 2026

Accepted. Mingyu Li is the first author and corresponding author.

Abs Bib PDF

Conventional robotic grasping in semi-structured service and workstation environments is often constrained by two physical bottlenecks: visual blind spots in rearward coverage and the bounded rotational range of traditional wrists. This paper presents an edge-native hand-wrist platform that addresses these coupled limitations through electromechanical co-design. We integrate a dorsal-ventral dual-camera relay for complementary front-rear perception with a direct-drive slip-ring mechanism enabling infinite continuous wrist roll. To support real-time operation on resource-constrained edge processors, the system features a reparameterized zero-shot detector that supports language-guided grasping while removing online text-encoding overhead via offline feature reparameterization. Kinematic and spatial validations in a predefined workstation-style setup indicate that the integrated platform can execute task-prior-driven grasp acquisitions for both forward and rearward targets entirely on the edge, without additional task-specific fine-tuning or cloud offloading.
@inproceedings{li2026icarm, title = {Hardware-Software Co-Design of a Dual-Vision, Infinite-Roll Hand for Edge-Native Grasping}, author = {Li, Mingyu and Gao, Zhixian and Guo, Zhangchi}, booktitle = {Proceedings of the IEEE International Conference on Advanced Robotics and Mechatronics (ICARM)}, location = {Paris, France}, year = {2026}, note = {Accepted. Mingyu Li is the first author and corresponding author.}, keywords = {Robotic grasping, Dexterous hand, Edge AI, Embedded vision, Hardware-software co-design, Zero-shot detection}, }