Papers
14
Total Citations
266
H-Index
8
About
Kenji Kato is a pioneering researcher at the intersection of assistive robotics, human-robot interaction, and elder care technology. His work spans two complementary frontiers: deploying care-support robots in real-world nursing facilities and advancing intelligent robotic systems through AI integration. Kato's most influential contribution — "Enhancing the LLM-Based Robot Manipulation Through Human-Robot Collaboration" (2024, 77 citations) — demonstrates his reach into cutting-edge AI, proposing novel frameworks for integrating large language models with physical robotic systems. His extensive body of work on transfer support robots, including longitudinal studies on devices like the Resyone and Hug, has generated significant evidence that robotic assistance can meaningfully reduce caregiver burden, improve resident mobility, and even increase verbal communication among nursing home residents — findings collectively accumulating over 100 citations. Kato has also explored socially assistive robots for dementia care, cane-type companion robots for gait stabilization, and markerless motion capture for biomechanical validation. His development of a Living Laboratory to test assistive technologies in simulated environments reflects a commitment to translating research into practical, real-world impact. Across disciplines, Kato's work offers vital insights for researchers, clinicians, and policymakers navigating the future of aging societies.
Research Focus
Key Achievements
Top Papers
- 1Enhancing the LLM-Based Robot Manipulation Through Human-Robot Collaboration77 citations · 2024
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