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About

Kae Doki is a robotics researcher whose work spans several interconnected domains, including miniature robotics, wearable assistive systems, mobile robot teleoperation, and intelligent autonomous control. Over more than two decades of scholarly contribution, Doki has made notable advances in piezoelectric-driven miniature robots, developing precise motion control and position measurement techniques using position-sensitive detectors and laser-based macro/micro tracking systems — foundational work that laid groundwork for small-scale robotic locomotion research. Doki's contributions to wearable power assist robotics are particularly significant, introducing pressure-distribution-based impedance control methods that meaningfully improved safety and efficacy in human-robot physical interaction across multi-joint body parts. This work addressed longstanding limitations in conventional assistive systems by incorporating real-time contact state feedback. More recently, Doki has explored augmented reality-enhanced teleoperation using 3D LiDAR technology to improve remote mobile robot operation, reflecting a forward-looking integration of perception and human-machine interface design. Across the research portfolio, probabilistic and information-theoretic methods — including Kullback-Leibler divergence for autonomous decision-making and robust localization — appear as recurring analytical tools. With citations accumulating across publications dating from 2001 to 2021, Doki's research represents a sustained and versatile contribution to applied robotics engineering.