Max Robotics — Global Service Robot Directory + US Certification

About

Yutaka Deguchi’s research lies at the intersection of autonomous robotics, human monitoring, and data-driven health assessment. His work focuses on developing low-cost, multi-robot systems that can autonomously track and analyze human movement to detect subtle health risks, particularly fall risk in elderly or vulnerable individuals. A key contribution is his pioneering use of skeleton clustering—where mobile robots equipped with Kinect sensors collaboratively capture and cluster skeletal data from multiple viewpoints to identify early signs of instability. His most cited papers, including “Towards Facilitating the Development of Monitoring Systems with Low-Cost Autonomous Mobile Robots” and “Skeleton Clustering by Multi-Robot Monitoring for Fall Risk Discovery,” each have garnered 9 citations, reflecting steady interest in his cost-effective, scalable approach. In his notable work “Multiple-robot monitoring system based on a service-oriented DBMS,” Deguchi demonstrated how two autonomous robots can coordinate positioning and monitoring angles to track a human subject in real time. His achievements include advancing the use of service-oriented architectures for robotic coordination and developing practical, low-cost monitoring solutions that bridge robotics and preventive healthcare.