Self-Position Estimation of an Autonomous Mobile Robot with Variable Processing Time

Abstract

This paper presents a new self-position estimation method of an autonomous mobile robot whose processing time can be variable. In this method, the current position of the robot is estimated with the image template matching with the normalized correlation coefficient between an 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. Moreover, in order to realize the efficient self-position estimation, image templates are generated with Genetic algorithm.In this paper, the usefulness of the proposed method is shown through some simulation results using test images and some experimental results using a real robot.