Self-Position Estimation of Autonomous Mobile Robot Considering Variable Processing Time

K. Doki, N. Isetani, A. Torii, and A. Ueda (Japan)


Selfposition Estimation, Anytime Sensing, Image tem plate Generations Autonomous mobile robot, Genetic algorithm


In this paper, we propose a new self-position estimation method for an autonomous mobile robot. This l'l'tethtxl is based on anytime sensing which harmonizes the time for the sensing and time for the action search in the action acquisition of an autonomous mobile robot by changing the processing time for sensing. In the self-msition estimation systems the position olthe robot is estimated by matching the input image at the current situation with the stored image templates which indicate certain positions. As a criterion of the template matching, the normalized correlation coefficient is applied. In order to realize the previous idea, the size of the image template can be varied in order to change the time for the self-position estimation. To realize a stable and efficient self-position estimation. an image template is generated with Genetic Algorithm. In this paper, the usefulness otthe proposed lnethod is shown through some experimental results with a real-robot.

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