Mehdi Fazilat
Papers
8
Total Citations
107
H-Index
6
About
Mehdi Fazilat is at the forefront of a revolutionary convergence between quantum computing and industrial robotics, pioneering novel approaches to solve some of the field's most intractable problems. His research centers on developing quantum-inspired algorithms and control systems to dramatically enhance the precision, efficiency, and intelligence of articulated robotic arms. Fazilat's major contributions include the creation of a groundbreaking quantum kinematic model based on quaternion/Pauli gate equivalence, which reimagines forward kinematics for six-jointed industrial arms like the ABB IRB 140. He has also advanced quantum-inspired sliding-mode control to mitigate chattering and computational overhead, and quantum neural networks for solving inverse kinematics and singularity avoidance. With his most cited paper garnering 35 citations and a growing body of work accumulating over 100 citations, Fazilat's impact is rapidly expanding. His notable achievements include developing a qubit rotation angle-based sliding mode controller and a Quantum Particle Swarm Optimization method for dynamic parameter identification, positioning him as a leading voice in the next generation of intelligent, quantum-enhanced robotic systems.
Research Focus
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