Chee Leong Chan

Institute for Infocomm Research, Agency for Science, Technology and Research

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About

Chee Leong Chan is a researcher whose work lies at the intersection of cognitive robotics and spatial intelligence, with a primary focus on indoor navigation and localization. His major contributions include the development of a novel cognitive navigation package that integrates topometric map representation with a three-level path planner, enabling robots to navigate complex indoor environments using architectural floor plans. This work, published in 2021 and garnering 9 citations, addresses the growing need for more human-like, cognitive models in autonomous navigation. Additionally, Chan has advanced Monte Carlo localization techniques by introducing a partial-map approach that leverages floor plan data, achieving robust localization even with incomplete environmental information. His research is particularly notable for bridging the gap between theoretical cognitive models and practical robotic applications, offering scalable solutions for real-world deployment in settings like hospitals, warehouses, and smart homes. By combining architectural priors with probabilistic algorithms, Chan’s work not only improves navigation efficiency but also reduces reliance on expensive sensor suites, making autonomous systems more accessible. His contributions are steadily gaining recognition in the robotics community, positioning him as an emerging voice in cognitive navigation and indoor spatial reasoning.