Genetic Bayesian ARAM for simultaneous localization and hybrid map building

Wei Hong Chin; Chu Kiong Loo; Naoyuki Kubota; Yuichiro Toda

doi:10.1109/SSCI.2015.48

Genetic Bayesian ARAM for simultaneous localization and hybrid map building

Wei Hong Chin, Chu Kiong Loo, Naoyuki Kubota, Yuichiro Toda

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

Abstract

This paper presents a new framework for mobile robot to perform localization and build topological-metric hybrid map simultaneously. The proposed framework termed as Genetic Bayesian ARAM consists of two main components: 1) Steady state genetic algorithm (SSGA) for self-localization and occupancy grid map building and 2) Bayesian Adaptive Resonance Associative Memory (ARAM) for topological map building. The proposed method is validated using a mobile robot. Result show that Genetic Bayesian ARAM capable of generate hybrid map online and perform localization simultaneously.

Original language	English
Title of host publication	Proceedings - 2015 IEEE Symposium Series on Computational Intelligence, SSCI 2015
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	275-279
Number of pages	5
ISBN (Electronic)	9781479975600
DOIs	https://doi.org/10.1109/SSCI.2015.48
Publication status	Published - Jan 1 2015
Externally published	Yes
Event	IEEE Symposium Series on Computational Intelligence, SSCI 2015 - Cape Town, South Africa Duration: Dec 8 2015 → Dec 10 2015

Other

Other	IEEE Symposium Series on Computational Intelligence, SSCI 2015
Country/Territory	South Africa
City	Cape Town
Period	12/8/15 → 12/10/15

ASJC Scopus subject areas

Artificial Intelligence

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10.1109/SSCI.2015.48

Cite this

Genetic Bayesian ARAM for simultaneous localization and hybrid map building. / Chin, Wei Hong; Loo, Chu Kiong; Kubota, Naoyuki et al.
Proceedings - 2015 IEEE Symposium Series on Computational Intelligence, SSCI 2015. Institute of Electrical and Electronics Engineers Inc., 2015. p. 275-279 7376621.

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

Chin, WH, Loo, CK, Kubota, N & Toda, Y 2015, Genetic Bayesian ARAM for simultaneous localization and hybrid map building. in Proceedings - 2015 IEEE Symposium Series on Computational Intelligence, SSCI 2015., 7376621, Institute of Electrical and Electronics Engineers Inc., pp. 275-279, IEEE Symposium Series on Computational Intelligence, SSCI 2015, Cape Town, South Africa, 12/8/15. https://doi.org/10.1109/SSCI.2015.48

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author = "Chin, {Wei Hong} and Loo, {Chu Kiong} and Naoyuki Kubota and Yuichiro Toda",

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Genetic Bayesian ARAM for simultaneous localization and hybrid map building

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