An acoustic sensor based novel method for 2D localization of a robot in a structured environment

Su, D; Ulapane, N; Wijerathna, B

An acoustic sensor based novel method for 2D localization of a robot in a structured environment

Su, D Ulapane, N

Wijerathna, B

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Publication Type:: Conference Proceeding
Citation:: Proceedings of the 2015 10th IEEE Conference on Industrial Electronics and Applications, ICIEA 2015, 2015, pp. 2024 - 2029
Issue Date:: 2015-11-20

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Field	Value	Language
dc.contributor.author	Su, D	en_US
dc.contributor.author	Ulapane, N https://orcid.org/0000-0003-3432-3943	en_US
dc.contributor.author	Wijerathna, B https://orcid.org/0000-0002-5087-4369	en_US
dc.date.issued	2015-11-20	en_US
dc.identifier.citation	Proceedings of the 2015 10th IEEE Conference on Industrial Electronics and Applications, ICIEA 2015, 2015, pp. 2024 - 2029	en_US
dc.identifier.isbn	9781467373173	en_US
dc.identifier.uri	http://hdl.handle.net/10453/47072
dc.description.abstract	© 2015 IEEE. Differences in locality in a structured environment cause variations in the reflection of an emitted acoustic wave. This paper exploits the above principle to propose a novel method of robot localization on a 2D map. The work brings novelty by using a simple acoustic emitter and a receiver for robot localization as opposed to exteroceptive sensors such as lasers, cameras, sonars and electromagnetic sensors which are conventionally used. This method requires only one sound emitter and a receiver in addition to odometry data to assist 2D localization of any mobile platform located in a pre-explored structured environment. The paper demonstrates the method through simulation by using Finite Element Analysis to solve the Helmholtz partial differential equation of acoustic wave propagation on a 2D map, and using a particle filter to correct the odometry through acoustic observations. Results show that the proposed method can effectively correct the odometry of a mobile platform in a structured environment. When compared with conventional exteroceptive sensors, compact installation and cost effectiveness come as practical advantages when implementing this method.	en_US
dc.relation.ispartof	Proceedings of the 2015 10th IEEE Conference on Industrial Electronics and Applications, ICIEA 2015	en_US
dc.relation.isbasedon	10.1109/ICIEA.2015.7334446	en_US
dc.title	An acoustic sensor based novel method for 2D localization of a robot in a structured environment	en_US
dc.type	Conference Proceeding
utslib.for	0906 Electrical and Electronic Engineering	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Students
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US

Abstract:

© 2015 IEEE. Differences in locality in a structured environment cause variations in the reflection of an emitted acoustic wave. This paper exploits the above principle to propose a novel method of robot localization on a 2D map. The work brings novelty by using a simple acoustic emitter and a receiver for robot localization as opposed to exteroceptive sensors such as lasers, cameras, sonars and electromagnetic sensors which are conventionally used. This method requires only one sound emitter and a receiver in addition to odometry data to assist 2D localization of any mobile platform located in a pre-explored structured environment. The paper demonstrates the method through simulation by using Finite Element Analysis to solve the Helmholtz partial differential equation of acoustic wave propagation on a 2D map, and using a particle filter to correct the odometry through acoustic observations. Results show that the proposed method can effectively correct the odometry of a mobile platform in a structured environment. When compared with conventional exteroceptive sensors, compact installation and cost effectiveness come as practical advantages when implementing this method.

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http://hdl.handle.net/10453/47072