A Spatial Attention-Based Behavior Coordination and Scaling Rule of Action Outputs of Mobile Robot in Dynamic Environment

摘要

With the arrival of an ultra-smart society, there is a need for mobility support robots that can act as flexibly as humans without trial-and-error learning and re-design of controllers in public spaces where people freely come and go. One of the solutions to this problem is to judge spaces that require suitable attention and make decisions based on only time-series observation information of the surrounding environment. Therefore, we propose a spatial attention-based behavior coordination rule to achieve safer avoidance by increasing the weight of avoidance behavior in advance when attention is paid to a moving obstacle, and a scaling rule of action outputs to adapt more quickly even to obstacles with faster moving speeds. We show the effectiveness of the proposed methods by comparing them with conventional methods through experiments using a real mobile robot.