Sakai Shiori
Papers
1
Total Citations
5
H-Index
1
About
Shiori Sakai is a researcher at the forefront of human-robot interaction, with a focused expertise in using non-contact sensing technologies to understand and respond to human behavior. Her work centers on developing intelligent dialog control methods for interface robots, leveraging spatial and motion data to create more natural and adaptive interactions. In her most-cited study, "Classification of age groups using walking data obtained from a Laser Range Scanner" (2016, 5 citations), Sakai pioneered a novel approach to human-robot interaction by measuring the distance between a sensor and a person as a time series, with the sensor placed at human waist height. This method enables robots to classify age groups based on walking patterns, a significant step toward socially aware robotics. By integrating Laser Range Scanner data into dialog control systems, Sakai’s contributions bridge the gap between raw sensor data and meaningful robotic responses, offering a foundation for future work in assistive and service robots. Her research stands out for its practical application of sensor fusion, demonstrating how subtle behavioral cues can enhance machine understanding of human users.
Research Focus
Key Achievements
Top Papers
- 1