Optimization-Based Path Planning for Person Following Using Following Field

Abstract

Person following is an essential task for a robot to serve a person. In an indoor environment, however, the following task can be failed due to the occlusion of the target by structures, e.g., walls or pillars. To address this problem, we propose a method that helps the robot follow the target well and rapidly re-detect the target after missing. The proposed method is an optimization-based path planning which uses a Following Field that we propose in this paper. The following field consists of two sub-fields: the repulsion field getting the robot out of the occluded area, and the target attraction field pushing the robot toward the target. We introduce how to construct the fields and how to integrate the field into a path optimization process. We show that our method works properly for following the target well in a maze consisting of various in-door features.