Learning localisation based on landmarks using self-organisation

Authors:
Kaustubh Chokshi;Stefan Wermter;Cornelius Weber
Affiliations:
Hybrid Intelligent Systems, School of Computing and Technology, University of Sunderland, Sunderland, United Kingdom;Hybrid Intelligent Systems, School of Computing and Technology, University of Sunderland, Sunderland, United Kingdom;Hybrid Intelligent Systems, School of Computing and Technology, University of Sunderland, Sunderland, United Kingdom
Venue:
ICANN/ICONIP'03 Proceedings of the 2003 joint international conference on Artificial neural networks and neural information processing
Year:
2003

Citing 6
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Abstract

In order to have an autonomous robot, the robot must be able to navigate independently within an environment. Place cells are cells that respond to the environment the animal is in. In this paper we present a model of place cells based on Self Organising Maps. The aim of this paper is to show that localisation can be performed even without having a built in map. The model presented shows that the landmarks are selected without any human interference. After training, a robot can localise itself within a learnt environment.