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About

Dmitry Zarubin’s research lies at the intersection of robot motion planning, topological representations, and manipulation in dynamic environments. His most influential work introduces topology-based representations that fundamentally alter how robots perceive and navigate spaces—by changing the Voronoi bias, metric, or topology of the motion space, his methods enable more robust planning and generalization during complex interactions, such as wrapping around obstacles. His 2013 paper on this topic has garnered 41 citations, underscoring its impact on the field. Zarubin also made notable contributions to robotic grasping, proposing a novel approach to synthesize caging grasps for objects with noisy geometry using geodesic balls, demonstrating success with realistic hand simulations. His hierarchical motion planning framework, published in 2012, further advanced the use of topological representations for multi-level reasoning. With over 85 total citations across his key works, Zarubin’s research provides foundational insights for students and researchers seeking to improve robot autonomy in cluttered, interactive settings—offering elegant mathematical tools to bridge perception and action.