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

  • 2024.May 14 :   A paper is accepted by Robotics: Science and Systems (RSS 2024).

  • 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。

  • 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  

T-RO Long paper
sym

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.

RCIM
sym

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.

T-ASE
sym

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.

T-Mech
sym

Construction of Interaction Parallel Manipulator: Towards Rehabilitation Massage

H. Dong, Y. Feng, Q. Chen, IM. Chen.

IEEE/ASME Transactions on Mechatronics(T-MECH), 2022.

RA-L
sym

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.

MMT
sym

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.

MMT
sym

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.

PR
sym

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.

RA-L
sym

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.

T-Mech
sym

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.

T-Mech
sym

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.

MMT
sym

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.

SORO
sym

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.

TITS
sym

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.

MMT
sym

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.

T-ASE
sym

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.

arXiv
sym

Bin Packing Optimization via Deep Reinforcement Learning

B. Wang, H. Dong

arXiv preprint arXiv:2403.12420(arXiv), 2024.

arXiv
sym

Bin Packing Optimization via Deep Reinforcement Learning

B. Wang, H. Dong

arXiv preprint arXiv:2403.12420(arXiv), 2024.

arXiv
sym

Discretizing SO (2)-Equivariant Features for Robotic Kitting

J Zhou, Y Zeng, H. Dong, I Chen</font></p>

arXiv preprint arXiv:2403.13336(arXiv), 2024.

</div> </div> ## *Conference papers*  
IROS 2018
sym

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.

IROS 2018 - RA-L
sym

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.

ICIP 2017
sym

Robust Ellipse Detection Via Arc Segmentation and Arc Classification

H. Dong, IM. Chen, and D. K. Prasad

International Conference on Image Processing(ICIP), 2017.

ICRA 2022
sym

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.

ICRA 2022
sym

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.

IROS 2022
sym

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.

IROS 2022 - RA-L
sym

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.

RSS 2024
sym

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.

# Grasp Lab ## *Constructing the Lab*   ### *• Current members*  
Snow

Huixu Dong, Principle Investigator(PI)

Forest

Jiadong Zhou, Ph.D. Student, my collaborator

at RRC of NTU, Singapore.

Robotic re-grasping

Mountains

Yue Feng, Ph.D. Student, my collaborator

at RRC of NTU, Singapore.

Interactive robotic manipulation

### *• Robot buddies*  
Snow
UR5
Forest
Panda
Mountains
Iiwa
## *Joining My Group*  
  • For current master's and undergraduate students with mechanical engineering, computer science, control engineering, electronics, mathematics mechanics, material and biology, and chemistry backgrounds at ZJU, please feel free to contact me by email (I am in general going to reply to emails on Friday or Saturday) if you are interested in joining my group.
  • For perspective PhD/master students, please apply to the Master/Ph.D. program in ME of ZJU and mention my name in application letters if you are interested in joining my group.
  • Also, 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、本科生加入机器人感知与抓取实验室, 感兴趣的同学请发邮件。
    ## *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.