About

M. Moghavvemi is a robotics and engineering researcher whose work spans robot kinematics, manipulator design, medical imaging systems, and brain-computer interfaces. With a career rooted in solving complex computational challenges in robotics, Moghavvemi has made notable contributions to motion planning and inverse kinematics for hyper-redundant and planar manipulators. His pioneering geometrical approaches to motion planning, introduced in 2009, offered elegant alternatives to computationally expensive traditional methods and remain among his most recognized work, accumulating 21 citations. Alongside kinematics, Moghavvemi has advanced manipulator design through torque minimization strategies, demonstrating how repositioning motors at the robot's base can yield lighter, more efficient robotic arms — insights reflected across multiple publications from 2012 to 2019. His research extends into medical technology, addressing line-of-sight challenges in optical image-guided neurosurgical systems, a clinically significant contribution cited 18 times. Moghavvemi has also explored brain-computer interfaces for robotic control and championed engineering education through LabVIEW-integrated laboratory modules. Across more than two decades, his interdisciplinary output reflects a commitment to making robotic systems smarter, lighter, and more accessible to both industry and the next generation of engineers.

Research Focus

Key Achievements

7
H-Index
10
Papers
100
Total Citations
10
Avg Citations/Paper
🏆 Most Cited Paper
Motion planning of hyper redundant manipulators based on a new geometrical method
21 citations · 2009
📈 Most Prolific Year: 2009 (4 Papers)
🤝 Key Collaborators: 16
🏛 Institutions: University of Nottingham Malaysia Campus, University of Science and Culture, University of Tehran, University of Malaya

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago