パーソナルモビリティの運転アシストのためのオンラインSLAMと人工ポテンシャル法に基づくShared Control

抄録

A passenger of a personal mobility is required to drive in such a way as to avoid obstacles and deviations from the sidewalk. In this paper, therefore, we focus on driving assistance through shared control by both the mobility and the passenger. Online SLAM through sensor fusion allows the mobility to build a map composed of 3D point clouds with drivable and non-drivable areas. Furthermore, an artificial potential field, considering the repulsion from non-drivable areas and attraction by the passenger, is generated in the map. The mobility is controlled to move in the gradient direction of the potential field. As a result, the experiments show that the mobility based on the shared controller is able to move toward a destination while avoiding an obstacle ahead and deviations from a drivable area.