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About

Ryosuke Mori is a robotics researcher whose work sits at the fascinating intersection of human motor behavior, autonomous systems, and machine learning. His research has made notable contributions to the field of mobile robotics, particularly in developing bio-inspired strategies that allow robots to replicate complex human athletic behaviors. Mori's most recognized work examines the LOT (Linear Optical Trajectory) strategy, a model originally proposed in human behavioral science to explain how outfielders catch fly balls, validating and implementing this theory through autonomous mobile robots. Building on this, he proposed the GAG (Gaining Angle of Gaze) strategy, an elegant solution enabling robots to track and intercept three-dimensional trajectories without requiring explicit spatial positioning data — a significant practical advancement. His research further extends to skill acquisition, investigating how robots equipped with monocular vision systems can learn ball-lifting tasks, illuminating parallels between machine learning and human motor skill development. Additionally, Mori contributed to robotic precision through neural network-based kinematic calibration using laser tracking systems. With citations spanning robotics, vision systems, and human movement science, his work offers valuable insights for researchers developing intelligent, adaptive robotic systems inspired by natural human cognition and movement.