Mojtaba Zarei
Papers
10
Total Citations
171
H-Index
7
About
Mojtaba Zarei’s research lies at the intersection of robotics, control systems, and cyber-physical systems, with a strong emphasis on experimental validation and real-time implementation. His major contributions include the dynamic identification and model-based control of haptic devices and parallel robots, notably the Novint Falcon haptic device, where he pioneered oscillation damping techniques using the phase trajectory length concept. His work on shared-control for mobile robots, combining haptic feedback with optimal velocity obstacle-based receding horizon control, has advanced human-robot interaction. Zarei has also made significant strides in the verification of learning-based cyber-physical systems, addressing scalability challenges in neural network-controlled systems. His most cited paper, “Experimental dynamic identification and model feed-forward control of Novint Falcon haptic device” (41 citations), exemplifies his hands-on approach to bridging theory and practice. With over 170 total citations, his research has influenced fields from haptics and parallel robotics to autonomous navigation and camera stabilization. Notable achievements include developing a real-time controller for a spherical parallel robot camera stabilizer using multi-thread programming and implementing vision-based control for spherical rolling robots. Zarei’s work is characterized by rigorous experimental studies, making his findings directly applicable to real-world robotic systems.
Research Focus
Key Achievements
Top Papers
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- 3Statistical verification of learning-based cyber-physical systems24 citations · 2020
- 4Dynamic identification of the Novint Falcon Haptic device23 citations · 2016
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