Tatsuki Harada

Sumitomo Heavy Industries (Japan), Tokyo University of Agriculture and Technology

Papers

Total Citations

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About

Tatsuki Harada is a leading researcher at the intersection of biomechanics and human-robot interaction, specializing in inverse optimal control and affective motion analysis. His work fundamentally addresses how humans generate movement—hypothesizing that our motions are optimal solutions to unknown, task-varying cost functions. Harada’s major contribution lies in developing computational frameworks that reverse-engineer these hidden objectives, enabling robots to interpret and replicate human-like behavior. His most-cited paper, "Human Motion Imitation using Optimal Control with Time-Varying Weights" (2021, 10 citations), introduces a novel method for robots to adapt their movements by learning time-dependent cost weights, bridging the gap between rigid robotic motion and fluid human action. In his earlier foundational work, "Analysis of Affective Human Motion During Functional Task Performance" (2019, 8 citations), Harada demonstrated that implicit emotional signals embedded in everyday tasks—like reaching or lifting—can be decoded and used to enhance robot communication. By quantifying how affective states shape movement, his research paves the way for more intuitive, socially aware collaborative robots. Harada’s contributions are critical for advancing assistive technologies and human-centered robotics, where understanding the nuanced interplay between emotion, intention, and motion is key to seamless human-machine teamwork.