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Título: | Mobile Robot Localization using Panoramic Vision and Combinations of Feature Region Detectors |
Autor: | Ramisa, Arnau CSIC ORCID; Tapus, Adriana; López de Mántaras, Ramón CSIC ORCID ; Toledo, Ricardo | Palabras clave: | Artificial intelligence Mobile robot Affine regions detectors Harris affine Hessian affine MSER SIFT GLOH Topological localization |
Fecha de publicación: | may-2008 | Editor: | Institute of Electrical and Electronics Engineers | Resumen: | This paper presents a vision-based approach for mobile robot localization. The environmental model is topological. The new approach uses a constellation of different types of affine covariant regions to characterize a place. This type of representation permits a reliable and distinctive environment modeling. The performance of the proposed approach is evaluated using a database of panoramic images from different rooms. Additionally, we compare different combinations of complementary feature region detectors to find the one that achieves the best results. Our experimental results show promising results for this new localization method. Additionally, similarly to what happens with single detectors, different combinations exhibit different strengths and weaknesses depending on the situation, suggesting that a context-aware method to combine the different detectors would improve the localization results. | Descripción: | IEEE International Conference on Robotics and Automation (ICRA 2008, Pasadena, California, May 19-23, 2008), pp. 538-543. | Versión del editor: | http://dx.doi.org/10.1109/ROBOT.2008.4543262 | URI: | http://hdl.handle.net/10261/3991 | DOI: | 10.1109/ROBOT.2008.4543262 | ISBN: | 978-1-4244-1646-2 | ISSN: | 1050-4729 |
Aparece en las colecciones: | (IIIA) Comunicaciones congresos |
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