Papers
3
Total Citations
83
H-Index
3
About
M. Benzaoui’s research focuses on the control and trajectory planning of redundant robotic manipulators, with a particular emphasis on enabling safe and efficient operation in constrained environments. His major contributions lie in developing algorithms that allow these robots to track precise trajectories while simultaneously avoiding obstacles—a critical challenge in industrial and service robotics. His most cited work, "Trajectory tracking with obstacle avoidance of redundant manipulator based on fuzzy inference systems" (2016, 59 citations), introduces an intelligent, fuzzy-logic-based approach to dynamically manage the robot’s self-motion for collision avoidance. Earlier foundational work, "Redundant robot manipulator control with obstacle avoidance using extended Jacobian method" (2010, 20 citations), established a robust kinematic framework by leveraging the self-motion vector within the inverse kinematic solution. Benzaoui also explored the critical issue of motion cyclicity in "Cyclic control of redundant robot under constraint with the self-motion method" (2008), comparing methods to prevent the loss of repeatable joint configurations. His research has significantly advanced the practical deployment of redundant manipulators, offering elegant solutions that balance primary task execution with real-time safety constraints.
Research Focus
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