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Proceedings Paper

Towards a multilevel cognitive probabilistic representation of space
Author(s): Adriana Tapus; Shrihari Vasudevan; Roland Siegwart
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Paper Abstract

This paper addresses the problem of perception and representation of space for a mobile agent. A probabilistic hierarchical framework is suggested as a solution to this problem. The method proposed is a combination of probabilistic belief with “Object Graph Models”(OGM). The world is viewed from a topological optic, in terms of objects and relationships between them. The hierarchical representation that we propose permits an efficient and reliable modeling of the information that the mobile agent would perceive from its environment. The integration of both navigational and interactional capabilities through efficient representation is also addressed. Experiments on a set of images taken from the real world that validate the approach are reported. This framework draws on the general understanding of human cognition and perception and contributes towards the overall efforts to build cognitive robot companions.

Paper Details

Date Published: 18 March 2005
PDF: 10 pages
Proc. SPIE 5666, Human Vision and Electronic Imaging X, (18 March 2005); doi: 10.1117/12.594487
Show Author Affiliations
Adriana Tapus, Ecole Polytechnique Federale de Lausanne (Switzerland)
Shrihari Vasudevan, Ecole Polytechnique Federale de Lausanne (Switzerland)
Roland Siegwart, Ecole Polytechnique Federale de Lausanne (Switzerland)

Published in SPIE Proceedings Vol. 5666:
Human Vision and Electronic Imaging X
Bernice E. Rogowitz; Thrasyvoulos N. Pappas; Scott J. Daly, Editor(s)

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