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About

Kenta Negishi’s research career is defined by pioneering contributions to robotics, particularly in the areas of master-slave teleoperation, assistive robotics, and visual servoing. His work has consistently focused on enhancing human-robot interaction, making robots more intuitive and effective in complex, real-world tasks. His most cited paper, "Defining a neural network controller structure for a rubbertuator robot" (2000, 21 citations), laid foundational work in soft robotics control. Negishi’s major contributions include developing novel methods to improve the maneuverability of master-slave systems by integrating visual feedback that accounts for human intention, as detailed in his 2016 paper (6 citations). This work aims to reproduce human skillfulness and dynamic performance in teleoperated robots. He also advanced the field of assistive robotics through his work on the ISAC system, a decentralized robotic feeding system for the disabled, where he developed a three-phase visual servoing algorithm for object grasping (2002, 3 citations). His research on lightweight, high-operable master devices (2015, 5 citations) further demonstrates his commitment to making teleoperation more accessible and effective for dangerous environments. Negishi’s career reflects a sustained dedication to bridging the gap between human capability and robotic performance.