Morphological independence for landmark detection in vision based SLAM

  • Ivan Villaverde*
  • , Manuel Graña
  • , Alicia D'Anjou
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

Morphologically independent vectors correspond to approximations to the vertices of the convex hull covering the data vectors in high dimensional space. We use Morphological Associative Memories (MAM) for the induction of sets of morphologically independent vectors from data. Simultaneous Localization and Mapping (SLAM) is the process of simultaneously building a map of the environment and localizing the mapping agent. In this paper we explore the realization of non-metric SLAM using a visual information based approach relying on morphologically independent images induced from a mobile robot camera image stream. The selected images are proposed as the landmarks for localization, building simultaneously a qualitative map of the environment. We report results of some experiments on data gathered from an indoor ambient.

Original languageEnglish
Title of host publicationComputational and Ambient Intelligence - 9th International Work-Conference on Artificial Neural Networks, IWANN 2007, Proceedings
PublisherSpringer Verlag
Pages847-854
Number of pages8
ISBN (Print)9783540730064
DOIs
Publication statusPublished - 2007
Externally publishedYes
Event9th International Work-Conference on Artificial Neural Networks, IWANN 2007 - San Sebastian, Spain
Duration: 20 Jun 200722 Jun 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4507 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference9th International Work-Conference on Artificial Neural Networks, IWANN 2007
Country/TerritorySpain
CitySan Sebastian
Period20/06/0722/06/07

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