Simulation-Based Behavior Planning to Prevent Congestion of Pedestrians Around a Robot

Abstract

Social robots working among pedestrians can attract crowds of people around them and consequently become bothersome entities causing congestion in narrow spaces. This in turn can affect the comfort of pedestrians who wish to pass through. To address this problem, our idea is to endow the robot with three capabilities: anticipating pedestrian crowding around the robot, understanding pedestrians' walking comfort, and planning to avoid congestions in advance. Combining several elementary pedestrian behavior models, the robot is able to simulate hypothetical situations where it navigates between pedestrians and anticipate the degree to which this would affect the pedestrians' walking comfort. During planning, the robot determines the best next navigation step based on the results of simulations. We tested the developed system in a real shopping mall and confirmed that it successfully reduces the robot's influence on pedestrian walking comfort due to congestions.