About

Guanwu Jiang is a robotics researcher whose work spans medical robotics, intelligent control systems, and human-robot collaboration. His research has made significant contributions to solving fundamental challenges in robot kinematics, precision positioning, and advanced control algorithms, accumulating over 170 citations across his published work. Jiang is perhaps best known for his pioneering application of PSO-optimized BP neural networks to solve inverse kinematics problems in puncture robots, a paper that has garnered 87 citations and demonstrated a compelling alternative to traditional geometric and algebraic methods. Building on this, he developed optical positioning systems using binocular vision for assisted puncture robots, advancing the accuracy and autonomy of minimally invasive surgical procedures. Beyond medical robotics, Jiang has made notable contributions to collaborative robot control, developing zero-moment teaching algorithms and general analytical solutions for 6-DOF cobots. His work on fuzzy backstepping control for dual-arm humanoid robots reflects a sustained interest in adaptive, intelligent control strategies capable of handling nonlinear dynamics and input saturation. Collectively, his research bridges theoretical robotics with practical clinical and industrial applications, making him a valuable contributor to the growing field of intelligent robotic systems.

Research Focus

Key Achievements

7
H-Index
15
Papers
187
Total Citations
12
Avg Citations/Paper
🏆 Most Cited Paper
A Precise Positioning Method for a Puncture Robot Based on a PSO-Optimized BP Neural Network Algorithm
87 citations · 2017
📈 Most Prolific Year: 2018 (3 Papers)
🤝 Key Collaborators: 18
🏛 Institutions: University of Science and Technology of China, Southwest University of Science and Technology, Chinese Academy of Sciences, Hefei Institutes of Physical Science

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago