Image Feature Significance for Self-position Estimation with Variable Processing Time

Kae Doki, Manabu Tanabe, Akihiro Torii, Akiteru Ueda

2009

Abstract

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 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.

References

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Paper Citation


in Harvard Style

Doki K., Tanabe M., Torii A. and Ueda A. (2009). Image Feature Significance for Self-position Estimation with Variable Processing Time . In Proceedings of the 5th International Workshop on Artificial Neural Networks and Intelligent Information Processing - Volume 1: Workshop ANNIIP, (ICINCO 2009) ISBN 978-989-674-002-3, pages 134-142. DOI: 10.5220/0002261001340142


in Bibtex Style

@conference{workshop anniip09,
author={Kae Doki and Manabu Tanabe and Akihiro Torii and Akiteru Ueda},
title={Image Feature Significance for Self-position Estimation with Variable Processing Time},
booktitle={Proceedings of the 5th International Workshop on Artificial Neural Networks and Intelligent Information Processing - Volume 1: Workshop ANNIIP, (ICINCO 2009)},
year={2009},
pages={134-142},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002261001340142},
isbn={978-989-674-002-3},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 5th International Workshop on Artificial Neural Networks and Intelligent Information Processing - Volume 1: Workshop ANNIIP, (ICINCO 2009)
TI - Image Feature Significance for Self-position Estimation with Variable Processing Time
SN - 978-989-674-002-3
AU - Doki K.
AU - Tanabe M.
AU - Torii A.
AU - Ueda A.
PY - 2009
SP - 134
EP - 142
DO - 10.5220/0002261001340142