Ryo Masaki
Papers
3
Total Citations
17
H-Index
3
About
Ryo Masaki is a leading researcher in human-robot interaction, specializing in remote control systems for mobile robots. His work centers on enhancing operator safety and precision through innovative force feedback and visual assistance technologies. Masaki’s most influential contribution is the development of a remote control method using a **collision prediction map**, which generates force feedback to intuitively warn operators of impending collisions, earning 9 citations. He further advanced this field by integrating **time-to-collision (TTC)** calculations into force assist systems, allowing robots to dynamically adjust feedback based on real-time environmental data and predicted trajectories. His 2022 study combined force and visual assists, addressing the limitations of single-modality feedback to improve both operability and safety. With over 17 citations across his key works, Masaki’s research has significantly improved the usability of teleoperated robots in hazardous or complex environments. His achievements include pioneering the fusion of predictive collision modeling with multimodal assistance, setting a new standard for intuitive and safe remote robot control.
Research Focus
Key Achievements
Top Papers
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