Self-Position Estimation with Variable Processing Time based on Image Feature Significance

K. Doki, M. Tanabe, A. Torii, and A. Ueda (Japan)


Image Feature Significance, Self-position Estimation, Vari able Processing Time, Autonomous Mobile Robot, Any time Sensing


We have researched about an action planning method of an autonomous mobile robot with a real-time search. In the action planning based on a real-time search, it is necessary to balance the time for sensing and time for action planning in order to use the limited computational resources efficiently. Therefore, we have studied on the sensing method whose processing time is variable and constructed a self position estimation system with variable processing time as an example of sensing. In this paper, we propose a self position estimation method of an autonomous mobile robot based on image feature significance. In this method, the processing time for self-position estimation can be varied by changing the number of image features. Stable position estimation can be realized even if the number of the image features is reduced because of its reduction based on its significance. To realize this concept, we conceive the concepts of the significance on image features, and verify three kinds of equations which respectively express the significance of image features. We examine them through some experimental results of self-position estimation with a real robot.

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