Mitsuru JINDAI
University of Toyama, Okayama Prefectural University, Ehime University
Papers
38
Total Citations
347
H-Index
12
About
Mitsuru Jindai is a robotics researcher whose work spans two interconnected domains: human-robot interaction and intelligent robot perception. His early and sustained contributions to social robotics are exemplified by his pioneering development of handshake robot systems, in which he meticulously analyzed the biomechanics and social dynamics of human handshaking to construct computational models governing approaching motion, shake-motion leading, and handshake request behaviors. This body of work, accumulating citations across multiple publications from 2006 to 2011, demonstrated that robots could engage in natural physical interaction without provoking discomfort in human partners — a critical milestone for service and welfare robotics. In his later research, Jindai shifted toward applying deep learning to practical robotics challenges, including object recognition for pick-and-place manipulation, robot grasping, and autonomous navigation using single-camera vision. Notably, his 2017 and 2018 studies introduced genetic algorithm optimization of deep belief neural network parameters, addressing a fundamental bottleneck in deploying deep learning systems on robotic platforms. His most-cited work on dynamic object pick-and-place (33 citations) further highlighted his commitment to user-friendly human-robot collaborative assembly. Collectively, Jindai's research bridges physical human-robot interaction with intelligent machine perception, advancing robots that are both socially responsive and autonomously capable.
Research Focus
Key Achievements
Top Papers
- 1
- 2Development of a shake-motion leading model for human-robot handshaking26 citations · 2008
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- 6Development of a Handshake Robot System for Embodied Interaction with Humans18 citations · 2006
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- 8A handshake robot system based on a shake-motion leading model15 citations · 2008
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