Graphical model inference algorithms for map sparsification

O. Sencan; H. Temeltas

doi:10.3182/20130916-2-tr-4042.00021

Graphical model inference algorithms for map sparsification

O. Sencan, H. Temeltas

Department of Control and Automation Engineering

Istanbul Technical University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-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 language	English
Title of host publication	1st IFAC Workshop on Advances in Control and Automation Theory for Transportation Applications, ACATTA 2013 - Proceedings
Publisher	IFAC Secretariat
Pages	205-210
Number of pages	6
Edition	PART 1
ISBN (Print)	9783902823519
DOIs	https://doi.org/10.3182/20130916-2-tr-4042.00021
Publication status	Published - 2013
Event	1st IFAC Workshop on Advances in Control and Automation Theory for Transportation Applications, ACATTA 2013 - Istanbul, Turkey Duration: 16 Sept 2013 → 17 Sept 2013

Publication series

Name	IFAC Proceedings Volumes (IFAC-PapersOnline)
Number	PART 1
Volume	1
ISSN (Print)	1474-6670

Conference

Conference	1st IFAC Workshop on Advances in Control and Automation Theory for Transportation Applications, ACATTA 2013
Country/Territory	Turkey
City	Istanbul
Period	16/09/13 → 17/09/13

Keywords

Bayes trees
Simultaneous localization and mapping
Sparse maps
Thin junction trees

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10.3182/20130916-2-tr-4042.00021

Cite this

Sencan, O., & Temeltas, H. (2013). Graphical model inference algorithms for map sparsification. In 1st IFAC Workshop on Advances in Control and Automation Theory for Transportation Applications, ACATTA 2013 - Proceedings (PART 1 ed., pp. 205-210). (IFAC Proceedings Volumes (IFAC-PapersOnline); Vol. 1, No. PART 1). IFAC Secretariat. https://doi.org/10.3182/20130916-2-tr-4042.00021

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title = "Graphical model inference algorithms for map sparsification",

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keywords = "Bayes trees, Simultaneous localization and mapping, Sparse maps, Thin junction trees",

author = "O. Sencan and H. Temeltas",

year = "2013",

doi = "10.3182/20130916-2-tr-4042.00021",

language = "English",

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series = "IFAC Proceedings Volumes (IFAC-PapersOnline)",

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Sencan, O & Temeltas, H 2013, Graphical model inference algorithms for map sparsification. in 1st IFAC Workshop on Advances in Control and Automation Theory for Transportation Applications, ACATTA 2013 - Proceedings. PART 1 edn, IFAC Proceedings Volumes (IFAC-PapersOnline), no. PART 1, vol. 1, IFAC Secretariat, pp. 205-210, 1st IFAC Workshop on Advances in Control and Automation Theory for Transportation Applications, ACATTA 2013, Istanbul, Turkey, 16/09/13. https://doi.org/10.3182/20130916-2-tr-4042.00021

Graphical model inference algorithms for map sparsification. / Sencan, O.; Temeltas, H.
1st IFAC Workshop on Advances in Control and Automation Theory for Transportation Applications, ACATTA 2013 - Proceedings. PART 1. ed. IFAC Secretariat, 2013. p. 205-210 (IFAC Proceedings Volumes (IFAC-PapersOnline); Vol. 1, No. PART 1).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - 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.

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Graphical model inference algorithms for map sparsification

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Keywords

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