Abstract
This paper describes a graph embedding procedure which extends the topologic information of a landmark graph with position estimates. The graph is used as an environment map for an autonomous agent, where the graph nodes contain information about places in two different ways: a panoramic image containing the landmark configuration and the estimated recording position. Calculation of the graph embedding is done with a modified “multidimensional scaling” algorithm, which makes use of distances and angles between nodes. It will be shown that especially graph circuits are responsible for preventing the path integration error from unbounded growth. Furthermore a heuristic for the MDS-algorithm is described, which makes this scheme applicable to the exploration of larger environments. The algorithm is tested with an agent building a map of a virtual environment.
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References
Benhamou S., Séguinot V.: How to find one’s way in the labyrinth of path integration models. J. theor. Biol. 174 (1995) 463–466
Cartwright B.A., Collet T.S.: Landmark learning in bees. Journal of Computational Physiology A 151 (1983) 521–543
Franz M.O., Schölkopf B., Mallot H.A., Bülthoff H.: Where did I take that snapshot? Scenebased homing by image matching. Biol. Cybernetics 79(3) (1998) 191–202
Kuipers B.: The spatial semantic hierarchy. Artifical Intelligence 119 (2000) 191–233
Mardia K.V., Kent J.T., Bibby J.M.: Multivariate Analysis. Academic Press, Inc., (1982) 413–415
Lu F., Milios, E.: Robot Pose Estimation in Unknown Environments by Matching 2D Range Scans. Journal of Intelligent and Robotic Systems 18 (1997) 249–275
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© 2002 Springer-Verlag Berlin Heidelberg
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Hübner, W., Mallot, H.A. (2002). Integration of Metric Place Relations in a Landmark Graph. In: Dorronsoro, J.R. (eds) Artificial Neural Networks — ICANN 2002. ICANN 2002. Lecture Notes in Computer Science, vol 2415. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-46084-5_134
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DOI: https://doi.org/10.1007/3-540-46084-5_134
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