Zhanwu Li

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About

Zhanwu Li is a leading researcher in multirobot systems and path planning, with a focus on optimizing coverage for autonomous agents in complex environments. His most-cited work, "Optimal Multirobot Coverage Path Planning: Ideal-Shaped Spanning Tree" (2018), has garnered 37 citations and addresses a critical challenge in robotics: how to efficiently coordinate multiple robots to cover a given area while avoiding obstacles. In this paper, Li introduces an improved ant colony optimization (ACO) algorithm to construct the best spanning tree, enabling single-robot coverage path planning (CPP) and then extending this approach to multirobot systems. His contributions are particularly valuable for applications in search-and-rescue, environmental monitoring, and automated inspection, where time and energy efficiency are paramount. By integrating bio-inspired optimization with geometric modeling, Li has advanced the theoretical foundations of coverage path planning, offering practical solutions for real-world robotics. His work continues to influence researchers in autonomous systems, multiagent coordination, and swarm robotics, making him a notable figure in the field.