Lei Che

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About

Lei Che is a researcher whose work bridges the gap between computational swarm intelligence and physical robotic systems. His key research areas include particle swarm optimization (PSO), mobile robot swarms, and the practical deployment of swarm algorithms in real-world environments. Che’s major contribution lies in rethinking the relationship between virtual particles and physical robots; he demonstrated that when a solution space corresponds to a real-world region, a robot swarm can effectively replace a particle swarm, enabling optimization to be performed through actual movement. His most-cited work, “Moving-Distance-Minimized PSO for Mobile Robot Swarm” (2021), has garnered 51 citations and is recognized for its novel approach to minimizing energy consumption during swarm-based optimization. This paper is notable for being one of the first to systematically treat robot motion as a direct analog to particle updates in PSO, opening new avenues for embodied intelligence. Che’s research is particularly impactful for students and researchers interested in the intersection of metaheuristics, robotics, and real-time autonomous systems, offering a compelling vision of how theoretical swarm models can be translated into tangible, moving agents.