Kentarou Hitomi
Papers
2
Total Citations
71
H-Index
2
About
Kentarou Hitomi’s research lies at the intersection of robotics, human behavior modeling, and intelligent locomotion, with a focus on enabling safe and adaptive human-robot interaction. His most cited work, “Development of pedestrian behavior model taking account of intention” (2012, 41 citations), addresses a critical challenge in robotics: predicting human movement in shared environments. By modeling pedestrian intentions, Hitomi’s framework allows robots to anticipate and navigate around people more naturally, a foundational contribution to autonomous navigation in crowded spaces. Earlier, his study “Reinforcement learning for quasi-passive dynamic walking of an unstable biped robot” (2006, 30 citations) advanced bipedal locomotion by applying reinforcement learning to achieve stable, energy-efficient walking on unstable platforms. This work demonstrated how machine learning can optimize complex robotic gaits without explicit programming. Hitomi’s contributions are particularly impactful for service robots, autonomous vehicles, and assistive technologies, where understanding human behavior and maintaining robust mobility are essential. His research continues to influence the development of socially aware robots that move safely and intuitively alongside people.
Research Focus
Key Achievements
Top Papers
- 1Development of pedestrian behavior model taking account of intention41 citations · 2012
- 2