Accurate localization with COAG features and self-adaptive energy region

Dong Il Kim; Jae Bok Song

doi:10.1007/978-3-642-40852-6-58

Accurate localization with COAG features and self-adaptive energy region

Dong Il Kim, Jae Bok Song

School of Mechanical Engineering

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

Abstract

Localization is very important for autonomous navigation of a mobile robot. For outdoor localization, Monte Carlo Localization (MCL) is used with the digital surface model. In order to develop an improved localization technique, in this study, commonly observed from air and ground (COAG) features are incorporated into an MCL localization system by means of an energy function to determine candidates. Experiments in real environments show improved localization accuracy over methods using MCL with COAG features.

Original language	English
Title of host publication	Intelligent Robotics and Applications - 6th International Conference, ICIRA 2013, Proceedings
Pages	576-583
Number of pages	8
Edition	PART 1
DOIs	https://doi.org/10.1007/978-3-642-40852-6-58
Publication status	Published - 2013
Event	6th International Conference on Intelligent Robotics and Applications, ICIRA 2013 - Busan, Korea, Republic of Duration: 2013 Sep 25 → 2013 Sep 28

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Number	PART 1
Volume	8102 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	6th International Conference on Intelligent Robotics and Applications, ICIRA 2013
Country	Korea, Republic of
City	Busan
Period	13/9/25 → 13/9/28

Keywords

MCL
Monte Carlo Localization

ASJC Scopus subject areas

Theoretical Computer Science
Computer Science(all)

Access to Document

10.1007/978-3-642-40852-6-58

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Cite this

Kim, D. I., & Song, J. B. (2013). Accurate localization with COAG features and self-adaptive energy region. In Intelligent Robotics and Applications - 6th International Conference, ICIRA 2013, Proceedings (PART 1 ed., pp. 576-583). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8102 LNAI, No. PART 1). https://doi.org/10.1007/978-3-642-40852-6-58

Accurate localization with COAG features and self-adaptive energy region. / Kim, Dong Il; Song, Jae Bok.

Intelligent Robotics and Applications - 6th International Conference, ICIRA 2013, Proceedings. PART 1. ed. 2013. p. 576-583 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8102 LNAI, No. PART 1).

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

Kim, DI & Song, JB 2013, Accurate localization with COAG features and self-adaptive energy region. in Intelligent Robotics and Applications - 6th International Conference, ICIRA 2013, Proceedings. PART 1 edn, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 1, vol. 8102 LNAI, pp. 576-583, 6th International Conference on Intelligent Robotics and Applications, ICIRA 2013, Busan, Korea, Republic of, 13/9/25. https://doi.org/10.1007/978-3-642-40852-6-58

Kim DI, Song JB. Accurate localization with COAG features and self-adaptive energy region. In Intelligent Robotics and Applications - 6th International Conference, ICIRA 2013, Proceedings. PART 1 ed. 2013. p. 576-583. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1). https://doi.org/10.1007/978-3-642-40852-6-58

Kim, Dong Il ; Song, Jae Bok. / Accurate localization with COAG features and self-adaptive energy region. Intelligent Robotics and Applications - 6th International Conference, ICIRA 2013, Proceedings. PART 1. ed. 2013. pp. 576-583 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1).

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