Y. Tabuchi
Papers
1
Total Citations
45
H-Index
1
About
Y. Tabuchi’s research focuses on human–robot interaction (HRI), mixed reality, and accessible robot training for non-expert users. Their most-cited work, a 2019 paper with 45 citations, addresses two fundamental challenges in service robotics: robots’ inability to grasp high-level context and humans’ difficulty intuiting a robot’s perceptual state. Tabuchi’s major contribution is a system that integrates mixed reality to bridge this communication gap, enabling non-experts to train robots intuitively in customer service environments like homes or retail spaces. By overlaying visual cues and feedback, the system allows humans to see what the robot “sees,” fostering more natural collaboration. This work stands out for its practical, user-centered approach, lowering barriers to robot deployment in everyday settings. Tabuchi’s research has implications for assistive robotics, smart environments, and inclusive design, demonstrating how augmented reality can make HRI more transparent and efficient. With growing interest in service robots, their contributions are increasingly cited in studies on mixed-reality interfaces and human-centered robotics.
Research Focus
Key Achievements
Top Papers
- 1