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About

Yuji Otoda’s research lies at the intersection of biomechanics and robotics, focusing on how humans and bipedal robots adapt their gait to asymmetric conditions. His most influential work explores the neural and mechanical principles behind split-belt treadmill walking—where the left and right belts move at different speeds—a paradigm used to study motor adaptation and cerebellar function. Otoda’s key contribution is the construction of a gait adaptation model that replicates human kinematic adjustments in a two-dimensional biped robot, bridging experimental neuroscience with robotic implementation. His 2009 paper on this topic has garnered 14 citations, serving as a foundational reference for researchers studying locomotor plasticity. Otoda also investigated energy-efficient walking by leveraging natural dynamics in torso-equipped biped robots, challenging conventional ZMP-based control methods. By modeling how healthy individuals and cerebellar patients differ in their adaptive responses, his work offers insights into rehabilitation robotics and motor recovery. Though his citation counts remain modest, Otoda’s interdisciplinary approach—merging human gait analysis with robotic simulation—has influenced subsequent studies on adaptive locomotion and bio-inspired control systems.