About

Dongyang Zhang is a robotics researcher focused on advancing manipulation, control, and perception for industrial and service robots. His work spans hand–eye calibration, adaptive force control, motion planning, and collision detection—critical areas for enabling robots to operate safely and precisely in unstructured environments. Zhang’s major contributions include a novel variable-height hand–eye calibration method that overcomes the “large up close, small from afar” imaging distortion, improving grasping accuracy for manipulators; an adaptive variable impedance hybrid force/position controller for large-surface polishing, which enhances surface finishing quality; and a compact robot-based defect detection device for silicon wafers, addressing a key challenge in semiconductor manufacturing. He has also developed a fast collision detection algorithm using sphere bounding boxes for six-degree-of-freedom manipulators and improved the PPO reinforcement learning algorithm for continuous robot gait control. With over 29 citations across his most-cited papers, Zhang’s research is gaining traction in both academic and applied robotics communities. His work on AGV chassis motion control and dynamic simulation of mechanical arms further demonstrates his commitment to bridging theory and practice in intelligent robotic systems.

Research Focus

Key Achievements

4
H-Index
7
Papers
29
Total Citations
4
Avg Citations/Paper
🏆 Most Cited Paper
Research on the Hand–Eye Calibration Method of Variable Height and Analysis of Experimental Results Based on Rigid Transformation
8 citations · 2022
📈 Most Prolific Year: 2024 (3 Papers)
🤝 Key Collaborators: 16
🏛 Institutions: Hangzhou Dianzi University, Shenyang Ligong University, Tianjin University of Science and Technology, Shenyang University of Technology

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago