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About

Obadiah Lam is a leading researcher in the intersection of robotics, spatial cognition, and human-robot interaction, with a primary focus on enabling robots to navigate real-world spaces using human-like, symbolic language. His most significant contribution is the development of the "abstract map," a novel construct that allows a mobile robot to interpret semantic descriptions—such as "find my office"—and purposefully navigate to unfamiliar rooms without prior exploration. This work, detailed in his highly cited 2015 paper "Robot navigation using human cues" (32 citations), represents the first complete symbolic goal-directed navigation system deployed on a physical robot. Lam further advanced this paradigm in his 2016 work "Find my office" (18 citations), demonstrating that robots can "imagine" a representative map from purely linguistic cues to navigate unseen environments. His research also extends to practical perception challenges, including a comparative evaluation of text recognition techniques for indoor robotics (7 citations) and automated extraction of navigable topometric graphs from floor plans (6 citations). By bridging the gap between human semantic understanding and robotic path planning, Lam’s work lays a critical foundation for more intuitive, language-driven robot assistants in complex indoor settings.