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About

Xuehou Tan is a researcher whose work lies at the intersection of computational geometry, robotics, and distributed algorithms. His primary research areas include polygon exploration, search and evacuation problems, and dominating set computation. Tan's most significant contribution is his foundational work on searching simple polygons using a "k-searcher," a concept that has garnered 18 citations and remains a key reference in the field of visibility-based pursuit-evasion. He has also advanced the understanding of online strategies for exploring unknown polygons, improving competitive ratios for autonomous agents navigating unfamiliar environments. In a notable 2016 study, Tan addressed the critical problem of evacuating people from an unknown convex region without prior knowledge of boundaries or positions, proposing competitive strategies to minimize evacuation path lengths. Additionally, his work on distributed algorithms for computing dominating sets on grids contributes to efficient network design. With a career spanning from early theoretical contributions to modern applications in emergency response, Tan's research continues to influence how autonomous systems perceive, navigate, and operate in uncertain spatial environments.