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About

Ahmed Bouzar Essaidi is a robotics researcher whose work centers on autonomous mobile robot systems, trajectory planning, and robotic structural design. His most significant contributions lie in the domain of wheeled mobile robots with trailers, where he has developed sophisticated dynamic optimization frameworks for generating efficient, minimum-time trajectories in indoor environments. His 2021 paper on minimum-time trajectory planning under dynamic constraints has garnered 29 citations, establishing him as a notable voice in autonomous robot motion planning. Earlier foundational work from 2015 explored dynamic modeling of car-like robots with trailers, addressing critical real-world phenomena such as skid and jack-knife instabilities by incorporating suspension systems and tire deformations into simulation models. More recently, Essaidi has expanded his research scope into structural optimization, introducing artificial neural network-based approaches for designing robot chassis frames resilient to random fatigue conditions — a practically significant challenge in robotics engineering. Collectively, his research bridges theoretical dynamic modeling with applied autonomous systems engineering, offering meaningful tools for the development of safer, more efficient mobile robotic platforms operating in complex environments.