Masaki Nakada

Waseda University, University of California, Los Angeles

Papers

Total Citations

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About

Masaki Nakada is a researcher at the intersection of robotics, biomechanics, and artificial intelligence, with key contributions to humanoid robot balance and biomimetic control systems. His most cited work, "Learning Arm Motion Strategies for Balance Recovery of Humanoid Robots" (2010, 11 citations), demonstrates how humans use arm motions to maintain stability—a principle he adapts for two-armed bipedal robots, offering a novel upper-body control strategy for disturbance rejection. This work has influenced the design of more agile, human-like robots. More recently, Nakada has pushed boundaries with "Deep Learning of Neuromuscular and Visuomotor Control of a Biomimetic Simulated Humanoid" (2020, 2 citations), where he introduces a framework that integrates a biomechanically simulated human musculoskeletal model with realistic eye movements and deep learning. This approach promises to bridge the gap between neuroscience and robotics, enabling more natural motor control. Though early in impact, this work signals a shift toward holistic, biologically inspired systems. Nakada’s research is especially valuable for students and researchers exploring how human motor strategies can inform next-generation humanoid robots.