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Por favor, use este identificador para citar o enlazar a este item: http://hdl.handle.net/10261/3991

Mobile Robot Localization using Panoramic Vision and Combinations of Feature Region Detectors

AutorRamisa, Arnau; Tapus, Adriana; López de Mántaras, Ramón ; Toledo, Ricardo
Palabras claveArtificial Intelligence
Mobile Robot
Affine Regions Detectors
Harris Affine
Hessian Affine
Topological Localization
Fecha de publicaciónmay-2008
EditorInstitute of Electrical and Electronics Engineers
ResumenThis 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.
DescripciónIEEE International Conference on Robotics and Automation (ICRA 2008, Pasadena, California, May 19-23, 2008), pp. 538-543.
Versión del editorhttp://dx.doi.org/10.1109/ROBOT.2008.4543262
Aparece en las colecciones: (IIIA) Comunicaciones congresos
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