About Me
From 2022, Huixu Dong is a “New Hundred-Talent Program” faculty (浙江大学新百人计划研究员/博导) in the Department of Mechanical Engineering at Zhejiang University, and the Director of Robotic Perception and Grasp Lab (RPGL) or Grasp Lab(GL) in short, and Dr.Dong obtained the title "Outstanding Overseas Youth"(国家高层次人才"海外优青"). I received the B.Sc degree in Mechatronics Engineering from Harbin Institute of Technology (HIT) in 2013 and obtained Ph.D. degree at Robotics Research Centre (RRC) of Nanyang Technological University (NTU) Singapore in 2018 advised by Prof.I-Ming Chen. Before joining Zhejiang University, I was a post-doctoral fellow of Robotics Institute (RI) at Carnegie Mellon University (CMU) and National University of Singapore (NUS).
Research Interests
I am mainly on robotic perception and manipulation, including general-purpose grasp, dynamic grasping, dexterous manipulation, and in-hand manipulation. I am interested in studying a challenging problem of efficiently understanding scenarios, reasoning about the grasping trajectory, and carrying out a reliable physical-environment grasping action for constructing an optimized system to perform robust manipulations for domestic, supermarket, warehouse and industrial setting applications. I am motivated by the above problem and working on offering highly resultful solutions through mathematical modeling, gripper design and control, visual perception as well as self-supervision robotic learning.
News
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2024.June 30 : Three papers on robotic perception and grasp are accepted by IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2024). Congratulations to Jiadong, Jihao, Keqi, Haotian.
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2024.May 14 : A paper is accepted by Robotics: Science and Systems (RSS 2024). Congratulations to Jihao and Keqi.
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2024.May 10 : My students Yicheng and Yanwen recieved offers from Imperial College and UC Berkeley, respectively. Yicheng 收到了英国帝国理工的Offer， Yanwen 收到了美国加州伯克利大学的Offer。
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2023.Jun 1 : In the 2023 "Jingdiao Cup" National University Graduation Design Competition, Ziyi won the individual gold medal (the only one nationwide), Keqi won the individual silver medal (ranked 2-9 nationwide) and also the Best Popularity Award, and Zhaohui won the first prize in the Eastern Region. 2023年度“精雕杯”全国大学生本科毕业设计大赛中，Ziyi荣获个人金奖（全国唯一），Keqi荣获个人银奖（全国排名2-9）并且荣获最佳人气奖，Zhaohui荣获东区一等奖。
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2022.Jun 15 : I have opened multiple fully-funded PostDoc, research associate (master's degree) and research officer (Bachelor's degree) positions in robotic perception and grasp. 欢迎具有机械电子、计算机、数学，控制、电子、力学、材料、生物、物理，化学等背景的博士后，博士，硕士、做毕业设计的本科生，计划出国读书的本科生等加入机器人感知与抓取实验室, 感兴趣的同学请发邮件。
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2022.Jun : After a 9-year wonderful and unforgettable time in Singapore and United States, I joined Zhejiang University ME to start my academic faculty journey.
Key Activities
- Associate Editor(AE), IEEE Transactions on Automation Science and Engineering (T-ASE) (2024 - 2026)
- Associate Editor(AE), IEEE Robotics and Automation Letters (RA-L) (2022 - 2025)
- Associate Editor(AE), IEEE International Conference on Robotics and Automation (ICRA 2023/2024)
- Associate Editor(AE), IEEE/RSJ International Conference on Intelligent Robots and Systems(IROS 2022/2023/2024)
- Associate Editor(AE), IEEE/ASME International Conference on Advanced Intelligent Mechatronics(AIM 2022/2023/2024)
- Member of T-Mech Junior Reviewers Program (TJRP), IEEE/ASME Transactions on Mechatronics(T-Mech 2021-2023)
Publications
Journal papers
Bin Packing Optimization via Deep Reinforcement Learning
B. Wang, H. Dong.
arXiv preprint arXiv:2403.12420(arXiv), 2024.
Discretizing SO (2)-Equivariant Features for Robotic Kitting
J. Zhou, Y. Zeng, H. Dong, IM. Chen.
arXiv preprint arXiv:2403.13336(arXiv), 2024.
Under-actuated Robotic Gripper with Multiple Grasping Modes Inspired by Human Finger
J Li, T Liao, H Nigatu, H Guo, G Lu, H. Dong.
arXiv preprint arXiv:2403.12502(arXiv), 2024.
Theoretical Model Construction of Deformation-Force for Soft Grippers Part I: Co-rotational Modeling and Force Control for Design Optimization
H Dong, H Guo, S Yang, C Qiu, J Dai, I Chen.
arXiv preprint arXiv:2303.12987(arXiv), 2024.
Theoretical Model Construction of Deformation-Force for Soft Grippers Part II: Displacement Control Based Intrinsic Force Sensing
H Dong, Z Zheng, H Guo, S Yang, C Qiu, J Dai, I Chen
arXiv preprint arXiv:2303.12418(arXiv), 2024.
Unveiling the Complete Variant of Spherical Robots
H Nigatu, L Jihao, G Shi, G Lu, H Dong
arXiv preprint arXiv:2403.03505(arXiv), 2024.
Real-time Robotic Manipulation of Cylindrical Objects in Dynamic Scenarios through Elliptic Shape Primitives
H. Dong, E. Asadi, G. Sun, D. K. Prasad, IM. Chen.
IEEE Transactions on Robotics(T-RO Long paper), 2018.
Geometric design optimization of an under-actuated tendon-driven robotic gripper
H. Dong, E. Asadi, C. Qiu, J. Dai, and IM. Chen.
Robotics and Computer-Integrated Manufacturing(RCIM), 2017.
Enabling Robotic Grasp: Object Pose Estimation via Pruned Hough Forest with Combined Split Schemes
H. Dong, DK Prasad, IM. Chen.
IEEE Transactions on Automation Science and Engineering(T-ASE), 2020.
Construction of Interaction Parallel Manipulator: Towards Rehabilitation Massage
H. Dong, Y. Feng, Q. Chen, IM. Chen.
IEEE/ASME Transactions on Mechatronics(T-MECH), 2022.
Fast Ellipse Detection for Robotic Manipulation of Cylindrical Objects
H. Dong, E. Asadi, C. Qiu, J. Dai, and IM. Chen.
IEEE Robotics and Automation Letters(RA-L), 2018.
Enabling grasp action: Generalized quality evaluation of grasp stability via contact stiffness from contact mechanics insight
H. Dong, C Qiu, DK Prasad, Y Pan, J Dai, IM Chen.
Mechanism and Machine Theory(MMT), 2019.
Grasp analysis and optimal design of robotic fingertip for two tendon-driven fingers
H. Dong, E. Asadi, C. Qiu, J. Dai, and IM. Chen.
Mechanism and Machine Theory(MMT), 2018.
Accurate detection of ellipses with false detection control at video rates using a gradient analysis
H. Dong, D. K. Prasad, and IM Chen.
Pattern Recognition(PR), 2017.
GSG: A Granary Soft Gripper with Mechanical Force Sensing via 3-Dimensional Snap-Through Structure
H. Dong, CY Chen, C Qiu, CH Yeow, H Yu.
IEEE Robotics and Automation Letters(RA-L), 2022.
Robotic Manipulations of Cylinders and Ellipsoids by Ellipse Detection with Domain Randomization
H. Dong, JD Zhou, C Qiu, P. K. Dilip, IM Chen.
IEEE/ASME Transactions on Mechatronics(T-MECH), 2022.
Real-time Avoidance Strategy of Dynamic Obstacles via Detection and Tracking with 2D Lidar for Mobile Robot
H. Dong, CY Weng, CQ Guo, H Yu, IM Chen.
IEEE/ASME Transactions on Mechatronics(T-MECH), 2020.
Repelling-screw-based geometrical interpretation of dualities of compliant mechanisms
H. Dong, K Wang, C Qiu, IM Chen, J Dai.
Mechanism and Machine Theory(MMT), 2021.
Bio-inspired Amphibious Origami Robot with Body Sensing for Multimodal Locomotion
H. Dong, HT Yang, S Ding, T Li, H Yu.
Soft Robotics(SORO), 2022.
Are object detection assessment criteria ready for maritime computer vision?
DK. Prasad, H. Dong, Deepu Rajan, and Chai Quek.
IEEE Transactions on Intelligent Transportation Systems(TITS), 2019.
A Repelling-Screw-Based Approach for the Construction of Generalized Jacobian Matrices for Nonredundant Parallel Manipulators
Kun Wang, H. Dong, Emmanouil Spyrakos-Papastavridis, Chen Qiu, Jian S. Dai.
Mechanism and Machine Theory(MMT), 2022.
Robotic Grasps of Cylindrical and Cubic Objects via Real-Time Learning-based Shape Detection
H. Dong, J. Zhou, H. Yu.
IEEE Transactions on Automation Science and Engineering(T-ASE), 2024.
Conference papers
Construction of a Multiple-DOF Underactuated Gripper with Force-Sensing via Deep Learning
Jihao Li, Keqi Zhu, Guodong Lu, I-Ming Chen, H. Dong
Robotics: Science and Systems · A Robotics Conference(RSS), 2024.
Efficient Pose Estimation from Single RGB-D Image via Hough Forest with Auto-context
H. Dong, D. K. Prasad, Q.Yuan, J.Zhou, E.Asadi, IM. Chen.
IEEE/RSJ International Conference on Intelligent Robots and Systems(IROS), 2018.
Fast Ellipse Detection for Robotic Manipulation of Cylindrical Objects
H. Dong, G.Sun, W.-C.Pang, E.Asadi, D.K.Prasad, IM. Chen
IEEE/RSJ International Conference on Intelligent Robots and Systems(IROS - RA-L), 2018.
Robust Ellipse Detection Via Arc Segmentation and Arc Classification
H. Dong, IM. Chen, and D. K. Prasad
International Conference on Image Processing(ICIP), 2017.
Learning-based Ellipse Detection for RoboticGrasps of Cylinders and Ellipsoids
H. Dong, J Zhou, C Qiu, DK Prasad, IM. Chen.
IEEE International Conference on Robotics and Automation(ICRA), 2022.
Estimation of Upper Limb Kinematics with a Magnetometer-Free Egocentric Visual-Inertial System
T Li, X Wu, H. Dong, Haoyong Yu.
IEEE International Conference on Robotics and Automation(ICRA), 2022.
Enabling Massage Actions : A n Interactive Parallel Robot with Compliant Joints
H. Dong, Y. Feng, C. Qiu, Y. Pan, M. He, IM. Chen.
IEEE/RSJ International Conference on Intelligent Robots and Systems(IROS), 2022.
GSG: A Granary-shaped Soft Gripper with Mechanical Sensing via Snap-Through Structure
H. Dong, C.Y. Chen, C. Qiu, C.H. Yeow, H.Y. Yu.
IEEE/RSJ International Conference on Intelligent Robots and Systems(IROS), 2022.
Grasp Lab
Constructing the Lab
• Current members
Huixu Dong, Principle Investigator(PI)
Jiadong Zhou, Ph.D. Student, my collaborator
at RRC of NTU, Singapore.
Robotic re-grasping
Yue Feng, Ph.D. Student, my collaborator
at RRC of NTU, Singapore.
Interactive robotic manipulation
• Robot buddies
Joining My Group
Target
It is well-known that a robotic grasping system significantly involves perception, modeling, gripper design and control, motion planning and materials, even emerging technologies such as VR and metaverse. Our research locates in those disciplines of robotic vision, mechatronics and motion planning. Our goal is to develop cutting-edge technologies of robotic perception and grasp to achieve domestic and industrial applications. To this end, we focus on (1) developing grippers with new concepts, new design, new control, new actuator, and new material; (2) studying real-time shape-based and 3D perceptions via mathematical modeling and machine learning; (3) investigating safe, interactive motion planning and grasping synthesis; (4) exploring supervision learning for robots commanding skills. Currently, we are working on robotic tidying, packaging, assembling, picking, placing, and re-grasping projects.
Supervising statement
The Grasp Lab is committed to fostering creativity, opening, inclusion, and collaboration among our members with diverse backgrounds. We strive to offer supportive environments for students to implement any novel ideas that break research borders, regardless of specific-purpose applications.Our lab highly encourages students to cooperate with other groups since robotics research is an interdisciplinary and collaborative endeavor. For each incoming member, we advise a suitable research direction and also, have a weekly meeting with each member. We set up a weekly meeting to inspire brainstorming, discuss literature studies and research ideas. Generally, we will allow students to do visiting students overseas such as RRC at NTU in Singapore, RI at CMU in United States, and some universities in Norway, Australia, England, Japan, and Finland.