Graphical model inference algorithms for map sparsification

O. Sencan, H. Temeltas

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

Abstract

This paper represents an approach to deal with graph-based map building by clustering the map features. the study will give an intuition about the sparsification of the map features using graph trees. Brief Survey and detailed examination of the subject is also given in the Methodology section. The study is concluded with simulation results and discussions.

Original languageEnglish
Title of host publication1st IFAC Workshop on Advances in Control and Automation Theory for Transportation Applications, ACATTA 2013 - Proceedings
PublisherIFAC Secretariat
Pages205-210
Number of pages6
EditionPART 1
ISBN (Print)9783902823519
DOIs
Publication statusPublished - 2013
Event1st IFAC Workshop on Advances in Control and Automation Theory for Transportation Applications, ACATTA 2013 - Istanbul, Turkey
Duration: 16 Sept 201317 Sept 2013

Publication series

NameIFAC Proceedings Volumes (IFAC-PapersOnline)
NumberPART 1
Volume1
ISSN (Print)1474-6670

Conference

Conference1st IFAC Workshop on Advances in Control and Automation Theory for Transportation Applications, ACATTA 2013
Country/TerritoryTurkey
CityIstanbul
Period16/09/1317/09/13

Keywords

  • Bayes trees
  • Simultaneous localization and mapping
  • Sparse maps
  • Thin junction trees

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