Model of Spatial Human-Agent Interaction with Consideration for Others

TL;DR

This paper presents a computational model for spatial human-agent interaction that accounts for consideration of others, validated through VR experiments showing how robot behavior influences human movement based on consideration levels.

Contribution

The study introduces a novel quantitative model of consideration in spatial interactions and validates it through human-virtual robot experiments in VR environments.

Findings

Higher consideration robots do not inhibit human movement.

Lower consideration robots inhibit human movement.

Robot approaching behavior reduces human movement regardless of consideration level.

Abstract

Communication robots often need to initiate conversations with people in public spaces. At the same time, such robots must not disturb pedestrians. To handle these two requirements, an agent needs to estimate the communication desires of others based on their behavior and then adjust its own communication activities accordingly. In this study, we construct a computational spatial interaction model that considers others. Consideration is expressed as a quantitative parameter: the amount of adjustment of one's internal state to the estimated internal state of the other. To validate the model, we experimented with a human and a virtual robot interacting in a VR environment. The results show that when the participant moves to the target, a virtual robot with a low consideration value inhibits the participant's movement, while a robot with a higher consideration value did not inhibit the participant's movement. When the participant approached the robot, the robot also exhibited approaching behavior, regardless of the consideration value, thus decreasing the participant's movement. These results appear to verify the proposed model's ability to clarify interactions with consideration for others.