Yingxin Kou

Papers

Total Citations

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About

Yingxin Kou is a leading researcher in multirobot systems and path planning, with a focus on optimizing coverage for autonomous robots in complex environments. Their most cited work, "Optimal Multirobot Coverage Path Planning: Ideal-Shaped Spanning Tree" (2018, 37 citations), introduces a novel approach that combines an improved ant colony optimization (ACO) algorithm with spanning tree theory to achieve optimal coverage paths for multiple robots navigating areas with obstacles. This contribution addresses a critical challenge in robotics—efficiently coordinating multiple agents to cover a space without redundancy or collision—and has been influential in advancing both theoretical and practical aspects of coverage path planning (CPP). Kou’s work stands out for its innovative integration of bio-inspired algorithms with geometric methods, offering a scalable solution that has inspired further research in swarm robotics and autonomous exploration. Their research has significant implications for applications like search-and-rescue, environmental monitoring, and automated inspection, where efficient multirobot coordination is essential. With a growing citation record, Yingxin Kou is recognized as a rising authority in optimization-driven robotics, bridging the gap between algorithmic theory and real-world deployment.