About

Dewei Yang is a leading researcher in surgical robotics and autonomous inspection systems, whose work bridges the gap between intelligent manipulation and real-world application. His primary contributions lie in the design of multidimensional force/torque sensors for surgical robots, where his comprehensive review has amassed 35 citations, establishing a foundational reference for enhancing surgical precision through haptic feedback. Yang has also pioneered novel robotic architectures for power line inspection, including a dual-parallelogram tri-arm robot that achieved 35 citations for its superior obstacle-crossing capabilities and vibration suppression control. His research extends to autonomous path planning, where he developed an improved particle swarm optimization algorithm (14 citations) for multi-target mobile robot navigation, and to surgical skill modeling using dynamical movement primitives (9 citations), enabling reusable suturing skill transfer for automated robotic surgery. Through optimization-based inverse kinematic analysis of minimally invasive surgical systems (8 citations), Yang has advanced the implementation of remote center of motion constraints. His work on tribrachiation robots and parallel robot calibration further demonstrates his commitment to solving complex kinematic challenges, making him a notable figure in both medical robotics and industrial automation.

Research Focus

Key Achievements

6
H-Index
8
Papers
115
Total Citations
14
Avg Citations/Paper
🏆 Most Cited Paper
Design and Application of Multidimensional Force/Torque Sensors in Surgical Robots: A Review
35 citations · 2023
📈 Most Prolific Year: 2023 (1 Papers)
🤝 Key Collaborators: 23
🏛 Institutions: Chongqing University of Posts and Telecommunications, Xi'an Jiaotong University, Chongqing Institute of Green and Intelligent Technology

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago