Yiploon Seow

Papers

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About

Yiploon Seow’s research focuses on advancing mobile robot localization, particularly by addressing the critical “kidnapped robot problem”—a scenario where a well-localized robot is suddenly displaced without warning. His most influential work, “Detecting and solving the kidnapped robot problem using laser range finder and wifi signal” (2017, 22 citations), introduces a novel hybrid approach that combines the high accuracy of laser rangefinder data with the global context provided by WiFi signals. This method not only detects when a robot has been moved but also enables rapid re-localization, overcoming a key limitation of traditional laser-based systems that fail in symmetrical indoor environments. In his related work, “Fast and robust localization using laser rangefinder and wifi data” (2017, 7 citations), Seow further refines this fusion technique, demonstrating how WiFi can break localization ambiguities caused by repetitive room layouts. His contributions are particularly valuable for real-world applications like warehouse automation and service robotics, where unexpected robot displacement is common. By integrating complementary sensing modalities, Seow has created more resilient localization systems that maintain accuracy even in challenging, symmetrical spaces.