Yogi Yamada
Papers
1
Total Citations
9
H-Index
1
About
Yogi Yamada is a leading researcher at the intersection of robotics, artificial intelligence, and gerontechnology, dedicated to enhancing safety and quality of life for the elderly. His primary research areas include assistive robotics, deep reinforcement learning, and human-robot interaction, with a focused application on fall prevention and risk mitigation. Yamada’s most notable contribution is the development of a novel framework for fall risk reduction using mobile assistant robots, as detailed in his highly cited 2018 paper. By integrating deep reinforcement learning with real-time risk analysis, his work enables robots to proactively predict and respond to slip-induced fall events, a leading cause of serious fractures in older adults. This approach represents a significant advancement over traditional reactive fall detection systems, offering a dynamic, intelligent solution that adapts to individual user behaviors and environmental conditions. With 9 citations, this foundational study has influenced subsequent research in proactive elderly care robotics, demonstrating Yamada’s impact in translating cutting-edge AI into practical, life-saving technologies. His work continues to inspire new directions in safe human-robot collaboration and personalized assistive systems.
Research Focus
Key Achievements
Top Papers
- 1