Evaluating the Impact of the Number of Access Points in Mobile Robots Localization Using Artificial Neural Networks

Pesin, Gustavo; Osorio, Fernando; Ueyama, Jo; Souza, Jefferson; Wolf, Denis; Braun, Torsten; Vargas, Patricia (2011). Evaluating the Impact of the Number of Access Points in Mobile Robots Localization Using Artificial Neural Networks. In: Fifth Internatiional Conference on Communication System software and middleware (COMSWARE), Verona, Italy (pp. 1-9). ACM 10.1145/2016551.2016561

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Localization is information of fundamental importance to carry out various tasks in the mobile robotic area. The exact degree of precision required in the localization depends on the nature of the task. The GPS provides global position estimation but is restricted to outdoor environments and has an inherent imprecision of a few meters. In indoor spaces, other sensors like lasers and cameras are commonly used for position estimation, but these require landmarks (or maps) in the environment and a fair amount of computation to process complex algorithms. These sensors also have a limited field of vision. Currently, Wireless Networks (WN) are widely available in indoor environments and can allow efficient global localization that requires relatively low computing resources. However, the inherent instability in the wireless signal prevents it from being used for very accurate position estimation. The growth in the number of Access Points (AP) increases the overlap signals areas and this could be a useful means of improving the precision of the localization. In this paper we evaluate the impact of the number of Access Points in mobile nodes localization using Artificial Neural Networks (ANN). We use three to eight APs as a source signal and show how the ANNs learn and generalize the data. Added to this, we evaluate the robustness of the ANNs and evaluate a heuristic to try to decrease the error in the localization. In order to validate our approach several ANNs topologies have been evaluated in experimental tests that were conducted with a mobile node in an indoor space.

Item Type:	Conference or Workshop Item (Paper)
Division/Institute:	08 Faculty of Science > Institute of Computer Science (INF) > Communication and Distributed Systems (CDS) 08 Faculty of Science > Institute of Computer Science (INF)
UniBE Contributor:	Braun, Torsten
ISBN:	978-1-4503-0560-0
Publisher:	ACM
Language:	English
Submitter:	Dimitrios Xenakis
Date Deposited:	04 Oct 2013 14:27
Last Modified:	05 Dec 2022 14:08
Publisher DOI:	10.1145/2016551.2016561
URI:	https://boris.unibe.ch/id/eprint/9972 (FactScience: 215792)