Michiaki Hirayama
Papers
3
Total Citations
47
H-Index
2
About
Michiaki Hirayama is a leading researcher in human-robot interaction and autonomous navigation, specializing in enabling mobile robots to operate safely and efficiently in human-crowded environments. His core contributions lie in developing advanced path-planning and motion-control algorithms that allow robots to anticipate, react to, and even physically influence human movement. Hirayama’s most influential work, the “Reactive, Proactive, and Inducible Proximal Crowd Robot Navigation Method” (30 citations), introduces a novel Inducible Social Force Model that enables robots to smoothly navigate dense crowds by predicting human trajectories, reacting to their movements, and using gentle physical nudges to avoid getting stuck. His “Dynamic Waypoint Navigation” framework (15 citations) further advances adaptive trajectory planning for human-symbiotic robots, offering model-based solutions that adapt to diverse passing scenarios with immediate planning. Recently, Hirayama has tackled the critical challenge of human velocity estimation (2024), using Kalman filters and least-squares methods with adjustable window sizes to filter out the periodic fluctuations of human gait and sensor vibrations. Collectively, his work bridges reactive and proactive navigation strategies, making him a key figure in the push toward truly autonomous robots that can share spaces with humans.
Research Focus
Key Achievements
Top Papers
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