Papers

5

Total Citations

27

H-Index

3

About

Nagisa Koyama’s research focuses on developing personal robots to support active, independent living—particularly for aging societies. Her core contributions lie in control systems and perception for wheeled inverted pendulum robots designed to follow and assist humans. Koyama pioneered a model predictive control (MPC) approach for posture stabilization and following control, enabling compact personal robots to maintain balance while tracking a user. Her work on robust user detection and tracking is equally notable: she developed a novel system using an omnidirectional camera and IR LED tags worn on the ankles, combined with a track-before-detect particle filter, to reliably identify and follow a target person in real time. Her most cited paper, “Following control approach based on model predictive control for wheeled inverted pendulum robot” (2016), has garnered 9 citations, while her related work on posture stabilization and IR tag tracking has accumulated over 15 citations collectively. Koyama’s research directly addresses the challenge of creating safe, unobtrusive robotic assistants that can transport belongings and accompany elderly individuals, thereby enhancing quality of life without diminishing physical activity. Her integrated approach—merging advanced control theory with practical sensing—represents a meaningful step toward personal robots that are both capable and socially beneficial.

Research Focus

Key Achievements

3
H-Index
5
Papers
27
Total Citations
5
Avg Citations/Paper
🏆 Most Cited Paper
Following control approach based on model predictive control for wheeled inverted pendulum robot
9 citations · 2016
📈 Most Prolific Year: 2016 (2 Papers)
🤝 Key Collaborators: 6
🏛 Institutions: Toyota Central Research and Development Laboratories (Japan), Toyota Motor Corporation (Switzerland)

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 15 days ago