Research Article
Evaluating the Impact of the Number of Access Points in Mobile Robots Localization Using Artificial Neural Networks
@INPROCEEDINGS{10.1145/2016551.2016561, author={J\^{o} Ueyama and Gustavo Pessin and Fernando Os\^{o}rio and Jefferson Souza and Denis Wolf and Torsten Braun and Patr\^{\i}cia Vargas}, title={Evaluating the Impact of the Number of Access Points in Mobile Robots Localization Using Artificial Neural Networks}, proceedings={5th International ICST Conference on COMmunication System softWAre and middlewaRE}, publisher={ACM}, proceedings_a={COMSWARE}, year={2012}, month={3}, keywords={wireless networks mobile robot localization artificial neural networks}, doi={10.1145/2016551.2016561} }- Jó Ueyama
Gustavo Pessin
Fernando Osório
Jefferson Souza
Denis Wolf
Torsten Braun
Patrícia Vargas
Year: 2012
Evaluating the Impact of the Number of Access Points in Mobile Robots Localization Using Artificial Neural Networks
COMSWARE
ACM
DOI: 10.1145/2016551.2016561
Abstract
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.
Copyright © 2011–2024 ACM
