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Mobile robot localization using panoramic vision and combinations of feature region detectors

Arnau Ramisa, Adriana Tapus, Ramón López de Mántaras, Ricardo Toledo

发表年份
2008
引用次数
22

摘要

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.

关键词

Computer scienceArtificial intelligenceComputer visionMobile robotDetectorContext (archaeology)Feature (linguistics)Representation (politics)RobotAffine transformation

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