Papers

6

Total Citations

70

H-Index

5

About

Xinglei Zhang is a leading researcher in surgical and hazardous-environment robotics, with a focus on inverse kinematics, singularity analysis, and cable-driven mechanisms. Their major contributions include developing an improved weighted gradient projection method for inverse kinematics of redundant surgical manipulators, which enhances end-effector pose accuracy critical for delicate operations—a work cited 24 times. Zhang also pioneered the "Lab-on-Robot" concept, creating an unmanned mass spectrometry robot for direct sample analysis in hazardous and radioactive environments, achieving 20 citations and demonstrating remote detection of gaseous, aerosol, liquid, and solid samples. Their analysis of singular configurations in robotic manipulators (11 citations) provides essential methods for identifying and avoiding performance-degrading singularities, particularly for serial manipulators not meeting the Pieper criterion. Additionally, Zhang has advanced variable stiffness mechanisms for wheelchair-mounted robotic manipulators (8 citations) and designed cable-driven hybrid joints with wrench-feasible workspace analysis (6 citations). Their latest work on an optimization algorithm for nonsingular kinematics using potential energy functions (2025) continues to push boundaries. Zhang’s research directly impacts surgical precision, remote hazardous environment operations, and assistive robotics, making their work highly relevant for students and researchers in medical robotics and autonomous systems.

Research Focus

Key Achievements

5
H-Index
6
Papers
70
Total Citations
12
Avg Citations/Paper
🏆 Most Cited Paper
An Improved Weighted Gradient Projection Method for Inverse Kinematics of Redundant Surgical Manipulators
24 citations · 2021
📈 Most Prolific Year: 2021 (2 Papers)
🤝 Key Collaborators: 14
🏛 Institutions: Zaozhuang University, East China University of Technology, Ocean University of China

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago