Self‐position estimation of an autonomous mobile robot with variable processing time

Abstract

SUMMARYThis paper presents a new self-position estimation method for an autonomous mobile robot whose processing time can be varied. In this method, the current position of the robot is estimated by image template matching with the normalized correlation coefficient between the input image and stored images. Based on the idea of anytime sensing, the time for self-position estimation can be varied by changing the image size. In order to realize efficient self-position estimation, image templates are generated by means of Genetic Algorithm. The usefulness of the proposed method is shown through simulation results using test images and experimental results obtained with a real robot.