Papers
6
Total Citations
105
H-Index
5
About
Modjtaba Rouhani is a robotics and intelligent systems researcher whose work spans swarm intelligence, adaptive control, and robotic motion planning. With a career stretching over two decades, Rouhani has made meaningful contributions to some of the most challenging problems in autonomous robotics and control theory. His most influential work focuses on swarm intelligence-based robotic search algorithms, with his 2021 paper on maze-like environment navigation accumulating 37 citations and a 2022 follow-up integrating game theory earning 16 more — reflecting sustained interest in decentralized, bio-inspired approaches to exploration. Earlier in his career, Rouhani pioneered neuro-adaptive control systems, developing a stability-guaranteed neural network controller for nonlinear robotic arms (2003, 28 citations), a contribution that helped lay groundwork for modern learning-based control architectures. His research portfolio also demonstrates breadth: from PSO-optimized PID control of inverted pendulums to solving inverse kinematics for redundant 7-DOF manipulators using constrained nonlinear optimization, and evolutionary gait generation for humanoid robots. Together, these works reflect a researcher consistently bridging classical control theory with computational intelligence — making Rouhani's contributions particularly valuable for students working at the intersection of robotics, optimization, and autonomous systems.
Research Focus
Key Achievements
Top Papers
- 1Swarm intelligence based robotic search in unknown maze-like environments37 citations · 2021
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