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About

Makoto Inaba is a pioneering robotics researcher whose work has profoundly shaped the fields of humanoid robotics, motion planning, and autonomous locomotion. Based at the University of Tokyo, Inaba has made landmark contributions to the development of intelligent humanoid platforms, most notably through the H6 and H7 robot series — integrated research systems designed to study perception-action coupling, bipedal locomotion, and real-time environmental interaction. His footstep planning algorithm for biped robots navigating obstacle-cluttered environments (192 citations) and his dynamic walking pattern generation method based on zero moment point optimization (158 citations) remain foundational references in legged robotics. Inaba's motion planning frameworks, which address both obstacle avoidance and dynamic balance constraints simultaneously, have influenced a generation of humanoid robot designers. His earlier work on impact control in robotic manipulators and distributed decision-making in cellular robotic systems demonstrates the remarkable breadth of his research vision. More unconventionally, his exploration of metamorphic robots using low melting point alloys points toward adaptive, reconfigurable robotic bodies. With multiple papers exceeding 100 citations and a body of work spanning manipulation, locomotion, and self-collision detection, Inaba stands as a central figure in modern humanoid robotics research.