Laser-Based Intersection-Aware Human Following With a Mobile Robot in Indoor Environments

Abstract

Human following in structured indoor environments has to face the challenge of full occlusion caused by the walls when the target person makes a turn at the corridor intersections. This may result in short-term, and even permanent loss of the target from the field of view of the robot. In this paper, human following with a mobile robot in presence of potential occlusions occurring at corridor intersections is addressed. The robot detects four different types of corridor intersections using the on-board laser scanner. Then, a potential-field-based human tracker is designed by integrating the intersection information into the potential function, in order to increase the visibility of the target, while maintaining the relative distance and orientation between the target and the robot. Simultaneously, the robot builds a multihypothesis topological map of the environment based on an improved generalized Voronoi graph, where the edges represent the corridors and the vertices are the virtual meet points extracted from the intersections. In such a way, simultaneous human following and topological mapping are achieved. Simulation and experimental results show that the proposed method can largely avoid occlusion of the target and obtain good performance of human following and topological mapping.