Ryosuke Kawabata
Papers
2
Total Citations
6
H-Index
2
About
Ryosuke Kawabata’s research lies at the intersection of human-robot interaction, gesture recognition, and informationally structured spaces. His core contributions focus on enabling more natural, cooperative communication between humans and robots through the detection and interpretation of pointing gestures. By integrating these gestures into systems that leverage structured environmental information, Kawabata has advanced the development of robots that can understand human intent without explicit verbal commands. His most-cited work, “Cooperative Human-Robot Interaction Based on Pointing Gesture in Informationally Structured Space” (2018, 4 citations), demonstrates how bodily expression can bridge the gap between human and machine, making interactions more intuitive and fluid. In a related study (2017, 2 citations), he explored how human-like motion and gesture detection allow robots to flexibly adapt to dynamic environments. Though his citation counts are modest, Kawabata’s work is foundational for researchers seeking to build socially aware robots that respond to nonverbal cues. His focus on practical, real-world applications—such as service robots in homes or workplaces—positions him as a contributor to the growing field of embodied AI and collaborative robotics.
Research Focus
Key Achievements
Top Papers
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- 2