Naomichi Otake
Papers
3
Total Citations
15
H-Index
2
About
Naomichi Otake is a robotics researcher whose work spans humanoid robot behavior development, machine learning, and human-robot interaction. His research uniquely bridges cognitive science and robotics engineering, with a particular focus on enabling robots to learn and adapt autonomously in dynamic environments. Otake's most notable contribution lies in his pioneering work on robotic imitation learning, most prominently demonstrated in his 2005 study developing imitation behaviors in the humanoid robot Kenta. By leveraging reinforcement learning and the concept of attentional focus during imitation, he advanced the understanding of how robots can autonomously develop and refine their behavioral repertoires — a paper that has garnered 11 citations and remains a foundational reference in developmental robotics. His more recent research shifts toward practical human-robot collaboration, particularly in the domain of mobile robot navigation. His work on smartphone-integrated human-following systems introduces innovative solutions combining Wi-Fi-based global trajectory tracking with walking motion signal matching for precise local following, demonstrating a commitment to real-world applicability and user-centered design. Across his career, Otake has consistently worked at the intersection of perception, learning, and mobility in robotics, contributing meaningful advances that support the development of socially aware, adaptive robotic systems.
Research Focus
Key Achievements
Top Papers
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