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About

Cen Zeng’s research focuses on advancing autonomous navigation and path planning for robotic systems, with a particular emphasis on mobile robots and free-floating space manipulators. His most significant contributions lie in the integration of genetic algorithms (GA) with classical pathfinding methods to solve complex, real-world navigation challenges. For instance, his highly cited work on "GA-based Global Path Planning for Mobile Robot Employing A* Algorithm" (25 citations) and its companion study (19 citations) pioneered a hybrid approach that combines MAKLINK graph theory, Dijkstra’s algorithm, and GA to generate optimal, collision-free paths in dynamic environments. Zeng further extended these concepts to space robotics, where he developed trajectory planning and obstacle avoidance strategies for free-floating manipulators used in on-orbit servicing (OOS)—a critical capability for satellite maintenance and space infrastructure assembly. His work on "Subsection Evolution in GA for Trajectory Planning of a Space Manipulator" and "Obstacle Avoidance Path Planning of Free-Floating Space Manipulator for On-Orbit Observation" demonstrates his ability to adapt terrestrial planning algorithms to the unique constraints of microgravity. With over 60 total citations, Zeng’s research bridges the gap between ground-based robotics and space exploration, offering practical solutions for autonomous systems in both domains.