publications

2025

1. arXiv

   

   TacRefineNet: Tactile-Only Grasp Refinement Between Arbitrary In-Hand Object Poses(IEEE RAL under review)

   Shuaijun Wang^*, Haoran Zhou, Diyun Xiang, and 1 more author

   arXiv preprint arXiv:2509.25746, 2025

   Abs Bib HTML Website

   This paper presents TacRefineNet, a novel approach for tactile-only grasp refinement that enables precise manipulation between arbitrary in-hand object poses using only tactile feedback.

   @article{wang2025tacrefinenet,
     title = {TacRefineNet: Tactile-Only Grasp Refinement Between Arbitrary In-Hand Object Poses(IEEE RAL under review)},
     author = {Wang, Shuaijun and Zhou, Haoran and Xiang, Diyun and You, Yangwei},
     journal = {arXiv preprint arXiv:2509.25746},
     year = {2025},
   }

2. arXiv

   

   DyDexHandover: Human-like Bimanual Dynamic Dexterous Handover using RGB-only Perception(ICRA2026 under review)

   Haoran Zhou, Yangwei You, and Shuaijun Wang^*

   arXiv preprint arXiv:2509.17350, 2025

   Abs Bib HTML Website

   This work presents DyDexHandover, a novel approach for human-like bimanual dynamic dexterous handover using only RGB perception, enabling natural and efficient object transfer between robotic hands.

   @article{zhou2025dydexhandover,
     title = {DyDexHandover: Human-like Bimanual Dynamic Dexterous Handover using RGB-only Perception(ICRA2026 under review)},
     author = {Zhou, Haoran and You, Yangwei and Wang, Shuaijun},
     journal = {arXiv preprint arXiv:2509.17350},
     year = {2025},
   }

2024

1. IJHR

   

   Learning an Image-Based Visual Servoing Controller for Object Grasping

   Shuaijun Wang, Lining Sun, Mantian Li, and 4 more authors

   International Journal of Humanoid Robotics, 2024

   SCI

   Abs DOI Bib HTML Video

   This paper presents a novel image-based visual servoing controller for object grasping that learns directly from visual feedback without requiring camera calibration or hand-eye transformation.

   @article{wang2024learning,
     title = {Learning an Image-Based Visual Servoing Controller for Object Grasping},
     author = {Wang, Shuaijun and Sun, Lining and Li, Mantian and Wang, Pengfei and Zha, Fusheng and Guo, Wei and Li, Qiang},
     journal = {International Journal of Humanoid Robotics},
     volume = {21},
     number = {05},
     pages = {2350033},
     year = {2024},
     publisher = {World Scientific},
     doi = {10.1142/S0219843623500337},
     note = {SCI}
   }

2023

1. Front. Neurorobot.

   

   Learning Adaptive Reaching and Pushing Skills Using Contact Information

   Shuaijun Wang, Lining Sun, Fusheng Zha, and 2 more authors

   Frontiers in Neurorobotics, 2023

   SCI Q2

   Abs DOI Bib HTML Video

   We develop a reinforcement learning-based pushing strategy using Soft Actor-Critic (SAC) with explicit contact modeling. The approach demonstrates improved generalization and training efficiency for contact-aware object manipulation tasks.

   @article{wang2023learning,
     title = {Learning Adaptive Reaching and Pushing Skills Using Contact Information},
     author = {Wang, Shuaijun and Sun, Lining and Zha, Fusheng and Guo, Wei and Wang, Pengfei},
     journal = {Frontiers in Neurorobotics},
     volume = {17},
     pages = {112976},
     year = {2023},
     publisher = {Frontiers Media SA},
     doi = {10.3389/fnbot.2023.1129076},
     note = {SCI Q2}
   }

2022

1. TMECH

   

   Learning Adaptive Grasping From Human Demonstrations

   Shuaijun Wang, Wenbin Hu, Lining Sun, and 2 more authors

   IEEE/ASME Transactions on Mechatronics, 2022

   SCI Q1

   Abs DOI Bib HTML Video

   This paper presents a learning-based approach to enable adaptive grasping from human demonstrations. We collect human teleoperation data and use supervised learning to train neural networks that can handle object variability in size and stiffness. The proposed method demonstrates robust performance across different object categories.

   @article{wang2022learning,
     title = {Learning Adaptive Grasping From Human Demonstrations},
     author = {Wang, Shuaijun and Hu, Wenbin and Sun, Lining and Wang, Xin and Li, Zhibin},
     journal = {IEEE/ASME Transactions on Mechatronics},
     volume = {27},
     number = {6},
     pages = {5148--5159},
     year = {2022},
     publisher = ieee,
     doi = {10.1109/TMECH.2022.3175885},
     note = {SCI Q1}
   }

2019

1. CYBER

   

   An Optimization-Based Direct Teaching Method for Manipulator with Tool’s Gravity Compensation

   Jingyuan Wu, Xin Wang, Shuaijun Wang, and 3 more authors

   In 2019 IEEE International Conference on Cybernetics and Intelligent Systems (CIS) and IEEE Conference on Robotics, Automation and Mechatronics (RAM), 2019

   EI Indexed

   Abs DOI Bib HTML

   This paper presents a direct teaching method for manipulators using force sensors with tool gravity compensation, enabling intuitive programming through demonstration.

   @inproceedings{wu2019optimization,
     title = {An Optimization-Based Direct Teaching Method for Manipulator with Tool's Gravity Compensation},
     author = {Wu, Jingyuan and Wang, Xin and Wang, Shuaijun and Wang, Shuaishuai and Zhan, Bo and Chen, Fei},
     booktitle = {2019 IEEE International Conference on Cybernetics and Intelligent Systems (CIS) and IEEE Conference on Robotics, Automation and Mechatronics (RAM)},
     pages = {196--201},
     year = {2019},
     organization = ieee,
     doi = {10.1109/CIS-RAM47153.2019.9095788},
     note = {EI Indexed}
   }

2017

1. ICARM

   

   A Generic Control Method of Manipulator Based on Optimization

   Shuaijun Wang, Lining Sun, Xin Wang, and 1 more author

   In 2017 2nd International Conference on Advanced Robotics and Mechatronics (ICARM), 2017

   EI Indexed

   Abs DOI Bib HTML

   This paper presents a quadratic programming-based control framework for manipulator trajectory tracking in both Cartesian and joint spaces. The method incorporates joint limits and obstacle avoidance constraints.

   @inproceedings{wang2017generic,
     title = {A Generic Control Method of Manipulator Based on Optimization},
     author = {Wang, Shuaijun and Sun, Lining and Wang, Xin and Zha, Fusheng},
     booktitle = {2017 2nd International Conference on Advanced Robotics and Mechatronics (ICARM)},
     pages = {504--509},
     year = {2017},
     organization = ieee,
     doi = {10.1109/ICARM.2017.8273223},
     note = {EI Indexed}
   }

2015

1. AMM

   Design and Research of a Novel Fast Connecting and Separating Modular Space Manipulator

   Shuai Jun Wang, Bo Zhang, Xin Wang, and 1 more author

   Applied Mechanics and Materials, 2015

   EI Indexed

   Abs DOI Bib

   This work presents the mechanical design and kinematic analysis of a novel modular space manipulator with fast connecting and separating capabilities.

   @article{wang2015design,
     title = {Design and Research of a Novel Fast Connecting and Separating Modular Space Manipulator},
     author = {Wang, Shuai Jun and Zhang, Bo and Wang, Xin and Wang, Xue Qian},
     journal = {Applied Mechanics and Materials},
     volume = {775},
     pages = {357--362},
     year = {2015},
     publisher = {Trans Tech Publ},
     doi = {10.4028/www.scientific.net/AMM.775.357},
     note = {EI Indexed}
   }

2. Modular Space Robotic Arm Joints and Robotic Arms That Can Be Used for Rapid Reconfiguration

   Xueqian Wang, Shuaijun Wang, Bo Zhang, and 2 more authors

   2015

   Chinese Patent, CN104647396A