Perceiving the Situation-Based Multi-Objective Fuzzy Control for Mobile Robot in Dynamic Environment

Abstract

With the advent of an ultra-smart society, it is desirable to have a mobile assistive robot that can act flexibly like a human without requiring prior information or trial-and-error learning, by appropriately judging the space to be paid attention to and making decisions using only time-series observation information of the surrounding area in public spaces where many people come and go freely. In conventional fuzzy control of mobile robots, the degree of danger was calculated using a membership function based on distance information at the current time for action control, which often failed to take time series into account, and in some cases failed to avoid moving obstacles. In the case of humans, approaches to avoidance are different because they take into account spatio-temporal relationships, such as whether an obstacle is approaching the human or only the human is approaching the obstacle. Therefore, it is thought that flexible behavior is realized by natural look-ahead, such as increasing the weight of the avoidance action in advance and starting the avoidance action, or paying appropriate attention to the approaching object, depending on the ever-changing situation. In order to achieve more flexible obstacle avoidance and target tracing behaviors like humans, we propose a multi-objective behavior coordination based on perceiving the situation and spatial attention-based sensory network, and verify the effectiveness of the proposed system.