Mohammad Biglarbegian
University of Guelph, University of Waterloo, Carleton University
Papers
26
Total Citations
791
H-Index
13
About
Mohammad Biglarbegian is a prominent robotics and intelligent systems researcher whose work spans robotic manipulation, autonomous mobile robots, fuzzy logic control, and agricultural robotics. He is perhaps best known for his highly cited 2016 survey on robotic grippers (233 citations), which comprehensively mapped the state of the art in robotic grasping technologies and their real-world applications. His foundational contributions to Type-2 fuzzy logic controllers — including novel interval Type-2 designs for modular and reconfigurable robots (142 citations) and a broader review of their applications (90 citations) — established him as a leading voice in intelligent, uncertainty-aware control systems. Biglarbegian has made significant advances in multi-robot systems, developing robust formation control strategies, conflict resolution methods for cluttered environments, and safe navigation frameworks for heterogeneous mobile robots. His work on docking-capable robot formations and tractor-trailer control systems reflects a deep commitment to solving complex, nonlinear robotics challenges with rigorous mathematical foundations backed by experimental validation. More recently, he has extended his expertise into smart agriculture, applying machine vision and learning to apple orchard yield prediction. With over 650 cumulative citations, his research consistently bridges theoretical innovation with practical, real-world impact across diverse and evolving domains of robotics.
Research Focus
Key Achievements
Top Papers
- 1State of the Art Robotic Grippers and Applications233 citations · 2016
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- 3Review of Recent Type-2 Fuzzy Controller Applications90 citations · 2016
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- 7A Novel Robust Leader-Following Control Design for Mobile Robots22 citations · 2012
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