Single 2D lidar based follow-me of mobile robot on hilly terrains

Abstract

It would be a very challenging task for mobile robot to track a person walking ahead on hilly terrains with a 2D lidar sensor instead of a 3D lidar or a rotating 2D lidar sensor. But it is clear that the 2D lidar based method is much more efficient in terms of computational costs and sensor cost only. For successful leader-following of the mobile robot with the 2D lidar sensor on such hilly roads, it is necessary to develop a classifier capable of recognizing a specific body part of the leader differently from other parts. In this study, the Mahalanobis distance kernel based on two features extracted from the leader’s torso profiles is used to construct the elliptical decision boundaries for the classification problem. In addition, based on that classifier, the roll and pitch angle of the 2D lidar sensor are controlled to continuously track the leader's body part and to estimate the relative distance between the leader and the robot. As a result, even when the leader walks along paths with flat-to-hill transitions in day and night, the mobile robot successfully follows the leader with 80 % detection rate by stable pitching not exceed 1° of the 2D lidar sensor for keeping the torso inside its field of view. The proposed approach will be useful to improve the performances of multi-sensor based leader detection system using not only lidar sensor but also vision sensor with switching control scheme.