Tatsuya Nakamura

Papers

Total Citations

H-Index

About

Tatsuya Nakamura is a robotics researcher whose work centers on mobile robot positioning and human-robot interaction, with a particular focus on sensor-based motion estimation and KANSEI—the Japanese concept of affective human perception. His most-cited contributions include pioneering methods for position estimation using novel accelerometer designs, offering advantages over traditional landmark, odometry, and GPS-based approaches by simplifying installation and enabling more flexible estimation. In his 1999 and 2002 papers, each garnering 2 citations, Nakamura introduced impedance-type detectors and acceleration sensors that laid groundwork for inertial navigation in mobile robotics. Expanding into human-centered robotics, his 2004 work quantitatively analyzed human KANSEI to generate motion algorithms that reduce user fatigue, using simulated red and blue ball interactions to study how robotic movement can feel more natural and less tiring. Though his citation counts are modest, Nakamura’s interdisciplinary approach—bridging sensor hardware development with affective computing—demonstrates an early commitment to making robots both technically capable and intuitively comfortable for human collaborators. His research remains relevant for students exploring low-cost positioning systems and human-aware motion planning.