Papers

47

Total Citations

1,268

H-Index

22

About

Saeed Behzadipour is a distinguished robotics researcher whose work spans cable-based parallel manipulators, human-robot interaction, and surgical robotics. He is perhaps best known for his foundational contributions to cable-driven robot design and analysis, including his highly cited 2005 study on the stiffness of cable-based parallel manipulators (206 citations), which established critical insights into how antagonistic forces influence design, control, and trajectory planning in these systems. His early work also introduced novel cable-based parallel robots with reduced degrees of freedom and an impressive ultra-high-speed cable robot capable of exceeding 120 pick-and-place cycles per minute, demonstrating both theoretical depth and practical engineering innovation. Behzadipour's research expanded into human-robot interaction, where he developed nonlinear model reference adaptive impedance control frameworks applicable to rehabilitation robotics (115 citations), and cooperative tele-rehabilitation systems using bilateral impedance control (68 citations). His work on force identification in robotic laparoscopic surgery further illustrates his range across medical robotics. More recently, he has applied robotics methodologies to industrial challenges such as heavy crane lift path planning in complex modular plants (57 citations). Collectively, his portfolio reflects a researcher who bridges elegant theoretical formulations with meaningful real-world applications across healthcare, manufacturing, and industrial automation.

Research Focus

Key Achievements

22
H-Index
47
Papers
1,268
Total Citations
27
Avg Citations/Paper
🏆 Most Cited Paper
Stiffness of Cable-based Parallel Manipulators With Application to Stability Analysis
206 citations · 2005
📈 Most Prolific Year: 2018 (5 Papers)
🤝 Key Collaborators: 60
🏛 Institutions: University of Waterloo, Sharif University of Technology, University of Alberta

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
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