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About

Min-Ge Lai is a robotics researcher whose work focuses on autonomous navigation, cooperative multi-robot systems, and fuzzy control in complex environments. Lai's research addresses one of the most challenging problems in mobile robotics: enabling multiple robots to collaboratively transport objects through unknown and obstacle-laden environments without prior map knowledge. Lai's most significant contribution is the development of evolutionary fuzzy control frameworks for cooperative robot navigation. The landmark 2014 paper, which has garnered 70 citations, introduced an innovative leader-follower architecture enabling two wheeled robots to dynamically switch between obstacle boundary following and target seeking behaviors, allowing seamless cooperative object transport in unpredictable environments. This work established a strong foundation for multi-robot coordination research. Building on this, Lai extended the framework to address concave map environments and the notoriously difficult dead-cycle problem — situations where robots become trapped in repetitive, unproductive movement patterns. Later work incorporated metaheuristic optimization techniques, fusing Ant Colony Optimization (ACO) and Particle Swarm Optimization (PSO) to evolve fuzzy controllers for three-robot cooperative systems navigating wall environments. Lai's research represents meaningful progress in intelligent autonomous systems, offering practical solutions for warehouse automation, search-and-rescue operations, and collaborative robotic transport scenarios.