Papers

9

Total Citations

111

H-Index

6

About

Amir Takhmar is a robotics researcher whose work spans bipedal locomotion, collision detection, and surgical robotics. He has made significant contributions to the planning, stability analysis, and control of biped robots, developing innovative approaches to gait planning on both flat and irregular terrain. His early work produced multiple control strategies for bipedal systems — including sliding mode control, Modified Transpose Jacobian control, and Cartesian-based gait planning — collectively earning over 65 citations and establishing him as a notable voice in humanoid robotics. A particularly influential contribution is his introduction of the Moment-Height Stability (MHS) measure, a novel metric for monitoring the dynamic postural equilibrium of biped robots. Beyond locomotion, Takhmar has addressed the practical challenges of industrial robotics, developing time-variant thresholds to counteract modeling errors in sensorless collision detection for robotic manipulators — his most cited work with 32 citations. More recently, he has extended his expertise into medical robotics, investigating haptic feedback in cooperative teleoperation systems for minimally invasive surgery. Together, his body of work reflects a researcher driven by both theoretical rigor and real-world applicability across diverse robotic domains.

Research Focus

Key Achievements

6
H-Index
9
Papers
111
Total Citations
12
Avg Citations/Paper
🏆 Most Cited Paper
Counteracting modeling errors for sensitive observer-based manipulator collision detection
32 citations · 2012
📈 Most Prolific Year: 2007 (4 Papers)
🤝 Key Collaborators: 7
🏛 Institutions: Western University, K.N.Toosi University of Technology

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago