Hough localization for mobile robots in polygonal environments

摘要

Knowing the position and orientation of a mobile robot situated in an environment is a critical element for effectively accomplishing complex tasks requiring autonomous navigation, and many techniques for robot self-localization have been extensively studied in the past. In this paper, we present a self-localization method that is based on the Hough transform for matching a geometric reference map with a representation of range information acquired by the robot's sensors. The technique is adequate for indoor office-like environments, especially for those environments that can be suitably represented by a set of segments. Many experiments are described to evaluate the effectiveness of the proposed method. Moreover, we have successfully tested this method in some dynamic environments populated with unknown and moving obstacles (e.g. persons or other robots moving around): office environments as well as the RoboCup environment.