Please use this identifier to cite or link to this item: http://dspace.mediu.edu.my:8181/xmlui/handle/10261/3991
Title: Mobile Robot Localization using Panoramic Vision and Combinations of Feature Region Detectors
Keywords: Artificial Intelligence
Mobile Robot
Affine Regions Detectors
Harris Affine
Hessian Affine
MSER
SIFT
GLOH
Topological Localization
Publisher: Institute of Electrical and Electronics Engineers
Description: IEEE International Conference on Robotics and Automation (ICRA 2008, Pasadena, California, May 19-23, 2008), pp. 538-543.
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.
This work was partially supported by USC Women in Science and Engineering (WiSE), the FI grant from the Generalitat de Catalunya, the European Social Fund, and the MID-CBR project grant TIN2006-15140-C03-01 and FEDER funds and the grant 2005-SGR-00093.
URI: http://dspace.mediu.edu.my:8181/xmlui/handle/10261/3991
Other Identifiers: 978-1-4244-1646-2
1050-4729
http://hdl.handle.net/10261/3991
10.1109/ROBOT.2008.4543262
Appears in Collections:Digital Csic

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