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Experimental Validation of an Evolutionary Method to Identify a Mobile Robot’s Position

  • Angel Kuri-Morales
  • Ignacio Lopez-Peña
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7329)

Abstract

A method to determine the position of a mobile robot using machine learning strategies was introduced in [1]. The method raises the possibility to decrease the size of database that holds the images that describe an area where a robot will localize itself. The present work does a statistical validation of the approach by calculating the Hamming and Euclidean distances between all the images using on the one hand all their pixels and on the other hand the reduced set of pixels obtained by the GA as described in [1]. To perform the analysis, a new series of images were taken from a specific position at several angles in both horizontal (pan) and vertical (tilt). These images were compared using two different measures: a) the Hamming distance and b) the Euclidean distance to determine how similar are one from another.

Keywords

Genetic Algorithms Multi-objective Optimization Machine Learning 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Angel Kuri-Morales
    • 1
  • Ignacio Lopez-Peña
    • 2
  1. 1.Departamento de ComputaciónInstituto Tecnológico Autónomo de MéxicoMexico CityMexico
  2. 2.Posgrado en Ciencia e Ingeniería de la ComputaciónIIMAS – UNAMMexico CityMexico

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