About

Heidar Ali Talebi is a prominent researcher whose work spans robotics, control systems, and autonomous vehicles, with particular expertise in adaptive and robust control strategies for complex mechanical systems. His most influential contributions center on impedance control and force/position control for robotic manipulators, including a widely cited 2017 study developing a robust adaptive model reference impedance controller capable of handling parameter uncertainties and actuator saturation in multi-link robotic arms (70 citations). His 2009 work on augmented hybrid impedance control for 7-DOF redundant manipulators (63 citations) further established his reputation in advanced robotic force control. Talebi has also made significant strides in neural network-based system identification, with a foundational 2006 paper on stable nonlinear system identification (53 citations) demonstrating both theoretical rigor and experimental validation. His research extends into teleoperation, where he has explored bilateral control under time delay and disturbance observers, as well as surgical robotics, contributing a notable multimodal training platform for the da Vinci surgical system. More recently, his work on UAV path planning using Bézier-Dubins curves and model predictive control for vehicle platoon maneuvers reflects the breadth and continued evolution of his research portfolio.

Research Focus

Key Achievements

17
H-Index
91
Papers
1,074
Total Citations
12
Avg Citations/Paper
🏆 Most Cited Paper
A Robust Adaptive Model Reference Impedance Control of a Robotic Manipulator With Actuator Saturation
70 citations · 2017
📈 Most Prolific Year: 2011 (18 Papers)
🤝 Key Collaborators: 104
🏛 Institutions: Western University, Amirkabir University of Technology, Concordia University, University of Tehran, National Taiwan University, University of Siena

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 42 days ago