Papers
4
Total Citations
74
H-Index
4
About
Satoshi Nishimura’s research lies at the intersection of physical human-robot interaction, variable-stiffness actuation, and socially assistive robotics. His most influential work focuses on impedance modulation—the ability to dynamically control a robot’s mechanical stiffness and force output for safer, more capable collaboration. In his 2022 paper on a macro-mini linear actuator using an electrorheological-fluid brake (33 citations), Nishimura introduced a novel antagonistic design that allows robots to deliver high forces when needed while maintaining low impedance for safe interaction. His 2021 study on a variable-stiffness spring mechanism (32 citations) further advanced this area by modeling an adjustable cantilever leaf spring for real-time stiffness modulation. Beyond physical interaction, Nishimura explores motion recognition using hidden Markov models (2014) and develops companion robots that enhance human well-being, such as a system that generates appropriate utterances for people watching television (2020). His work bridges hardware innovation and human-centered design, earning recognition for enabling robots that are both powerful and gentle—a critical balance for future collaborative and assistive applications.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3A classification method of motion database using hidden Markov model5 citations · 2014
- 4Utterance Function for Companion Robot for Humans Watching Television4 citations · 2020