Localization for mobile robots using panoramic vision, local features and particle filter

Andreasson, H. and Treptow, A. and Duckett, T. (2005) Localization for mobile robots using panoramic vision, local features and particle filter. In: 2005 IEEE International Converence on Robotics and Automation: ICRA - 2005, 18 - 22 April 2005, Barcelona, Spain.

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Item Type:Conference or Workshop contribution (Paper)
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Abstract

In this paper we present a vision-based approach to self-localization that uses a novel scheme to integrate feature-based matching of panoramic images with Monte Carlo localization. A specially modified version of Lowe’s SIFT algorithm is used to match features extracted from local interest points in the image, rather than using global features calculated from the whole image. Experiments conducted in a large, populated indoor environment (up to 5 persons visible) over a period of several months demonstrate the robustness of the approach, including kidnapping and occlusion of up to 90% of the robot’s field of view.

Keywords:navigation, self-localisation, mobile robotics
Subjects:G Mathematical and Computer Sciences > G700 Artificial Intelligence
Divisions:College of Science > School of Computer Science
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ID Code:29074
Deposited On:06 Nov 2017 16:43

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