A Spatial Attention-Based Sensory Network for Fuzzy Controller of Mobile Robot in Dynamic Environments

With the emergence of an ultra-smart society, it is desirable to have a mobility support robot that can act flexibly like a human without prior knowledge or trial-and-error learning. One solution is to appropriately judge the space to be paid attention to and make decisions using only time-series observation information of the surrounding area in public spaces where many people come and go freely. Our goal is to use a spatial-attention-based sensory network for a fuzzy controller to adapt to dynamic environments and safely perform complex navigation tasks using only time-series observation information, without requiring prior knowledge such as the type, speed, and direction of moving obstacles, and more importantly, without trial-and-error learning or control system redesign. The computer simulation results show that the proposed spatial attention-based sensory network and situation-based behavior coordination allow the mobility support robot to adapt online to a complex dynamic environment with multiple moving obstacles. In addition, the proposed method can perform the navigation task more safely and efficiently than the conventional method.