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About

Chaobin Xu is an emerging researcher in the field of robotics and intelligent control, with a primary focus on mobile robot path planning, trajectory tracking, and autonomous cleaning systems. His most notable contribution is the development of an improved genetic algorithm for mobile robot path planning, which addresses critical limitations of traditional approaches—such as slow convergence and poor dynamic adaptability—by introducing a dichotomy-based multi-step population initialization method. This work has already garnered 11 citations since its publication in 2025, reflecting its timely relevance. Xu has also advanced the control of cost-effective three-wheeled independent drive and steering (3WID3WIS) mobile robots, employing dynamic model predictive control to enhance trajectory tracking performance, a study that has attracted 7 citations. Additionally, his theoretical and simulation work on negative pressure adsorption for wall-climbing cleaning robots demonstrates his versatility in applying robotics to practical construction and maintenance challenges. Through these contributions, Xu is establishing himself as a thoughtful innovator in autonomous mobile robotics, with a clear trajectory toward impactful, application-driven research.