Shohei Yamamoto

University of Fukui, Hiroshima University

Papers

Total Citations

H-Index

About

Shohei Yamamoto is a robotics and automation researcher whose work bridges human-robot interaction and industrial manufacturing efficiency. His primary research areas include biped humanoid robotics, real-time motion imitation, and quality prediction for automated painting systems. Yamamoto’s most notable contribution is the development of a real-time posture imitation system for biped humanoid robots using particle filters and simple joint control for standing stabilization. This work, published in 2016 and cited 9 times, addresses the challenge of estimating robot joint angles from human demonstrations without direct measurement, enabling more intuitive robot learning and stable bipedal locomotion. More recently, Yamamoto has focused on industrial applications, designing a database-driven quality predictor for painting systems in excavator manufacturing. This 2022 study, with 2 citations, tackles labor shortages by optimizing painting robot performance through predictive quality control. Yamamoto’s work demonstrates a commitment to advancing both the theoretical foundations of humanoid robotics and the practical implementation of intelligent automation in manufacturing, making him a valuable contributor to the fields of robotics, control systems, and industrial engineering.