Abstract
Place recognition is important navigation ability for autonomous navigation of mobile robots. Visual cues extracted from images provide a way to represent and recognize visited places. In this article, a multi-cue based place learning algorithm is proposed. The algorithm has been evaluated on a localization image database containing different variations of scenes under different weather conditions taken by moving the robot-mounted camera in an indoor-environment. The results suggest that joining the features obtained from different cues provide better representation than using a single feature cue.
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Siddiqui, R., Lindley, C. (2012). Multi-Cue Based Place Learning for Mobile Robot Navigation. In: Kamel, M., Karray, F., Hagras, H. (eds) Autonomous and Intelligent Systems. AIS 2012. Lecture Notes in Computer Science(), vol 7326. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31368-4_7
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DOI: https://doi.org/10.1007/978-3-642-31368-4_7
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