Lihong Ma

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About

Lihong Ma is a pioneering researcher in robotics and motion planning under uncertainty, best known for foundational work on optimal strategies for visual exploration in constrained environments. Her key research areas include algorithmic robotics, sensor-based navigation, and competitive analysis of motion strategies. Ma's major contributions center on solving the "looking around a corner" problem—determining the most efficient path for a robot equipped with a vision system to observe a hidden area behind an obstacle. Her 1994 paper, "An Optimal Competitive Strategy for Looking Around a Corner" (6 citations), and her 1993 work, "The Optimal Way for Looking Around a Corner" (4 citations), established rigorous theoretical frameworks for minimizing worst-case travel distance when a robot must navigate around polygonal obstacles or wedges with unknown angles. These studies introduced competitive ratio analysis to visual exploration tasks, influencing subsequent research in autonomous navigation and surveillance. Though her citation counts are modest, Ma's work is notable for its mathematical elegance and practical relevance to early robotics challenges, providing foundational insights that continue to inform modern approaches to sensor-based motion planning in partially observable environments.