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About

Michael W. Lanighan is a roboticist whose research centers on dexterous mobile manipulation, task planning, and human-robot interaction. His most influential work, the UMass uBot concept (20 citations), redefines robotic dexterity by drawing on Bernstein’s classic definition—emphasizing the ability to solve motor problems correctly, quickly, and resourcefully. Lanighan’s development of Generalized Affordance Templates (9 citations) provides a standardized, augmented-reality-enhanced framework for defining manipulation tasks, enabling intuitive human-in-the-loop operation. He also tackles the challenge of grounding symbolic planning in real-world uncertainty, as seen in his work on hybrid task planning grounded in belief (5 citations). Beyond these contributions, Lanighan demonstrated practical ingenuity with “Lego Plays Chess,” a low-cost robotic chess agent built from Lego NXT bricks that competed in the AAAI 2011 Small Scale Manipulation Challenge. His path planning research for dexterous mobility further addresses the complexity of integrating sensory and motor options under runtime constraints. With a career spanning foundational concepts in mobile manipulation to accessible, low-cost robotics, Lanighan’s work bridges theory and practice, offering valuable tools and insights for researchers and students advancing intelligent, resourceful robotic systems.