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About

Sue Whitesides is a prominent computer scientist whose research sits at the intersection of computational geometry, motion planning, and robotics. Her foundational work in the 1980s on planar linkages and the "mover's problem" — examining how robot arms navigate 2-dimensional bounded regions — established critical complexity-theoretic frameworks for understanding robotic movement, with her 1984 paper on 2-dimensional linkages accumulating over 100 citations and her companion studies adding dozens more. These contributions helped shape the theoretical underpinnings of modern robot motion planning. Whitesides further advanced the field through her investigations of curvature-constrained path planning, demonstrating how a robot with bounded turning radius can find optimal collision-free paths within convex polygons — work that has garnered nearly 80 citations and remains relevant to autonomous vehicle navigation. Her research on robot localization, exploring how a robot can determine its position in a known environment with minimum travel, reflects her consistent focus on practical algorithmic challenges. Beyond technical research, she has contributed to pedagogy through collaborative problem-solving curricula at the graduate level. Across more than two decades of scholarship, Whitesides has built an influential body of work that bridges theoretical computer science and real-world robotics applications.