Abstract
Morphologically independent vectors correspond to approximations to the vertices of the convex hull covering the data vectors in high dimensional space. We use Morphological Associative Memories (MAM) for the induction of sets of morphologically independent vectors from data. Simultaneous Localization and Mapping (SLAM) is the process of simultaneously building a map of the environment and localizing the mapping agent. In this paper we explore the realization of non-metric SLAM using a visual information based approach relying on morphologically independent images induced from a mobile robot camera image stream. The selected images are proposed as the landmarks for localization, building simultaneously a qualitative map of the environment. We report results of some experiments on data gathered from an indoor ambient.
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Villaverde, I., Graña, M., d’Anjou, A. (2007). Morphological Independence for Landmark Detection in Vision Based SLAM. In: Sandoval, F., Prieto, A., Cabestany, J., Graña, M. (eds) Computational and Ambient Intelligence. IWANN 2007. Lecture Notes in Computer Science, vol 4507. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73007-1_102
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DOI: https://doi.org/10.1007/978-3-540-73007-1_102
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