Investigation on the evolution of an indoor robotic localization system based on wireless networks

Gustavo Pessin*, Fernando S. Osorio, Jefferson R. Souza, Jo Ueyama, Fausto G. Costa, Denis F Wolf, Desislava Dimitrova, Torsten Braun, Patricia A Vargas

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)

Abstract

This work addresses the evolution of an artificial neural network (ANN) to assist in the problem of indoor robotic localization. We investigate the design and building of an autonomous localization system based on information gathered from wireless networks (WN). The article focuses on the evolved ANN, which provides the position of a robot in a space, as in a Cartesian coordinate system, corroborating with the evolutionary robotic research area and showing its practical viability. The proposed system was tested in several experiments, evaluating not only the impact of different evolutionary computation parameters but also the role of the transfer functions on the evolution of the ANN. Results show that slight variations in the parameters lead to significant differences on the evolution process and, therefore, in the accuracy of the robot position.

Original languageEnglish
Pages (from-to)743-758
Number of pages16
JournalApplied Artificial Intelligence
Volume27
Issue number8
DOIs
Publication statusPublished - 2013

Keywords

  • OPTIMIZATION

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