Human understanding technologies essential for advancing autonomous systems, and interaction design for training support and behavior modification in human–autonomous system collaboration.
Aiming for effective collaboration between humans and autonomous/smart systems—such as communication robots, cleaning and delivery robots, and autonomous vehicles—our research focuses on human understanding technologies essential for their advancement, including estimation of concentration and interest and evaluation of impressions toward robot behaviors (i.e., how people feel and respond). Furthermore, we are developing interaction designs for training support and behavior modification using VR simulators and robots to facilitate human support through collaboration.
As communication robots, service robots, and autonomous vehicles become increasingly integrated into society, opportunities for humans to collaborate with autonomous systems are expanding. In such collaborations, it is not sufficient for systems merely to execute tasks; they must understand human behavior and internal states, consider how their actions are interpreted by humans, and respond appropriately.
As essential technologies for collaboration, we study human understanding methods such as estimating concentration and interest from facial images and gaze, estimating visual recognition (whether a target object was perceived) based on the relationship between gaze and surrounding environment, and evaluating impressions of robot behavior to understand human internal states and perceptions.
Additionally, to support humans through collaboration, we are developing a VR emergency driving simulator to measure driving behavior and evaluate driving skills, designing robot arm movements for psychologically interactive games, and exploring safe driving support through implicit behavior modulation by controlling engine sounds—all as part of our research in interaction design.
We will continue to deepen our research on fundamental technologies while advancing applied studies on human support through collaboration with autonomous systems, aiming to realize a framework in which humans and autonomous systems can collaborate naturally.
| Research | |
|---|---|
| Journal | Adjunct Proceedings of the 17th International Conference on Automotive User Interfaces and Interactive Vehicular Applications (AutomotiveUI '25) |
| Title | Preliminary Study on Implicit Driving Behavior Modulation via Engine Sound Modification |
| Author | Sota Inoue, Akira Utsumi, Hirotake Yamazoe |
| URL | https://dl.acm.org/doi/10.1145/3744335.3758488 |
Learn about the cutting-edge research achievements, advanced technical resources, and know-how that the Graduate School of Engineering at the University of Hyogo can provide. We welcome partners who can create the future together with us by jointly generating new ideas and technologies through collaborative research, commissioned research, and technical consultations.
More
