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About

Naser Azim Mohseni is a robotics researcher whose work centers on motion planning, trajectory optimization, and autonomous mobile robot navigation. His research has made meaningful contributions to the field of omni-directional mobile robotics, particularly in developing computationally efficient methods for navigating complex environments with static obstacles while respecting real-world physical constraints such as velocity and acceleration limits. Mohseni's most recognized contribution, "Optimal Trajectory Planning for an Omni-Directional Mobile Robot with Static Obstacles: A Polynomial Based Approach" (2015), has garnered 13 citations and introduces an elegant polynomial-based framework that reformulates trajectory planning as an optimal control problem. This approach offers a practical balance between mathematical rigor and computational tractability. His subsequent works in 2016 and 2017, each cited 6 times, extend this foundation by applying direct optimal control solutions and low-computational motion planning strategies, reinforcing his commitment to bridging theoretical optimization with deployable robotic systems. Collectively, his body of work addresses a critical challenge in robotics: enabling robots to move efficiently and safely in real environments. His research is particularly valuable for students and engineers working on autonomous navigation, path planning algorithms, and mobile robot control systems.