Lattice independent component analysis for mobile robot localization

  • Ivan Villaverde*
  • , Borja Fernandez-Gauna
  • , Ekaitz Zulueta
  • *Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

4 Citations (Scopus)

Abstract

This paper introduces an approach to appearance based mobile robot localization using Lattice Independent Component Analysis (LICA). The Endmember Induction Heuristic Algorithm (EIHA) is used to select a set of Strong Lattice Independent (SLI) vectors, which can be assumed to be Affine Independent, and therefore candidates to be the endmembers of the data. Selected endmembers are used to compute the linear unmixing of the robot's acquired images. The resulting mixing coefficients are used as feature vectors for view recognition through classification. We show on a sample path experiment that our approach can recognise the localization of the robot and we compare the results with the Independent Component Analysis (ICA).

Original languageEnglish
Pages (from-to)335-342
Number of pages8
JournalLecture Notes in Computer Science
Volume6077 LNAI
Issue numberPART 2
DOIs
Publication statusPublished - 2010
Externally publishedYes
Event5th International Conference on Hybrid Artificial Intelligence Systems, HAIS 2010 - San Sebastian, Spain
Duration: 23 Jun 201025 Jun 2010

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