Evaluation of an efficient approach for target tracking from acoustic imagery for the perception system of an autonomous underwater vehicle

Autores
Villar, Sebastian Aldo; Acosta, Gerardo Gabriel; Sousa, André L.; Rozenfeld, Alejandro Fabian
Año de publicación
2013
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
This article describes the core algorithms of the perception system to be included within an autonomous underwater vehicle (AUV). This perception system is based on the acoustic data acquired from a side scan sonar (SSS). These data should be processed in an efficient time, so as to the perception system could detect and recognize a predefined target. This detection and recognition outcome is then an important piece of knowledge for the AUV's dynamic mission planner (DMP). Effectively, the DMP should propose different trajectories, navigation depths and other parameters that will change the robot's behavior, according to the perception system output. Hence, the time to make a decision is critical to assure safe robot operation and to acquire good quality data, and consequently the efficiency of the on-line image processing from acoustic data, is a key issue. Current techniques for acoustic data processing are time and computationally intensive. Hence, it was decided to process data coming from a SSS using a technique that is used for radars, due to its efficiency and its amenability to on-line processing. The engineering problem to solve in this case, is underwater pipeline tracking for routinely inspections in the off-shore industry. Then, an automatic oil pipeline detection system was developed borrowing techniques from processing of radar measurements. The radar technique is known as Cell Average-Constant False Alarm Rate (CA-CFAR). With a slight variation of the algorithms underlying this radar technique, consisting of the previous accumulation of partial sums, a great improvement in computing time and effort is achieved. Finally, a comparison with previous approaches over images acquired with a SSS from a vessel in the Salvador de Bahia bay in Brazil, showed the feasibility of using this on-board technique for AUV perception.
Fil: Villar, Sebastian Aldo. Universidad Nacional del Centro de la Provincia de Bs.as.. Facultad de Ingenieria Olavarria. Departamento de Electromecanica. Grupo Intelymec; Argentina; Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina;
Fil: Acosta, Gerardo Gabriel. Universidad de Las Islas Baleares. Departamento de Fisica; España; Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ingenieria Olavarria. Departamento de Electromecanica. Grupo Intelymec; Argentina;
Fil: Sousa, André L.. Universidad de Las Islas Baleares. Departamento de Fisica; España;
Fil: Rozenfeld, Alejandro Fabian. Universidad de Las Islas Baleares. Departamento de Fisica; España; Universidad Nacional del Centro de la Provincia de Bs.as.. Facultad de Ingenieria Olavarria. Departamento de Electromecanica. Grupo Intelymec; Argentina;
Materia
CA-CFAR
SIDE-SCAN SONAR
AUTOMATIC OBJETIVE DETECTION
SONAR IMAGERY
AUV
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/1135

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oai_identifier_str oai:ri.conicet.gov.ar:11336/1135
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Evaluation of an efficient approach for target tracking from acoustic imagery for the perception system of an autonomous underwater vehicleVillar, Sebastian AldoAcosta, Gerardo GabrielSousa, André L.Rozenfeld, Alejandro FabianCA-CFARSIDE-SCAN SONARAUTOMATIC OBJETIVE DETECTIONSONAR IMAGERYAUVhttps://purl.org/becyt/ford/2.2https://purl.org/becyt/ford/2This article describes the core algorithms of the perception system to be included within an autonomous underwater vehicle (AUV). This perception system is based on the acoustic data acquired from a side scan sonar (SSS). These data should be processed in an efficient time, so as to the perception system could detect and recognize a predefined target. This detection and recognition outcome is then an important piece of knowledge for the AUV's dynamic mission planner (DMP). Effectively, the DMP should propose different trajectories, navigation depths and other parameters that will change the robot's behavior, according to the perception system output. Hence, the time to make a decision is critical to assure safe robot operation and to acquire good quality data, and consequently the efficiency of the on-line image processing from acoustic data, is a key issue. Current techniques for acoustic data processing are time and computationally intensive. Hence, it was decided to process data coming from a SSS using a technique that is used for radars, due to its efficiency and its amenability to on-line processing. The engineering problem to solve in this case, is underwater pipeline tracking for routinely inspections in the off-shore industry. Then, an automatic oil pipeline detection system was developed borrowing techniques from processing of radar measurements. The radar technique is known as Cell Average-Constant False Alarm Rate (CA-CFAR). With a slight variation of the algorithms underlying this radar technique, consisting of the previous accumulation of partial sums, a great improvement in computing time and effort is achieved. Finally, a comparison with previous approaches over images acquired with a SSS from a vessel in the Salvador de Bahia bay in Brazil, showed the feasibility of using this on-board technique for AUV perception.Fil: Villar, Sebastian Aldo. Universidad Nacional del Centro de la Provincia de Bs.as.. Facultad de Ingenieria Olavarria. Departamento de Electromecanica. Grupo Intelymec; Argentina; Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina;Fil: Acosta, Gerardo Gabriel. Universidad de Las Islas Baleares. Departamento de Fisica; España; Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ingenieria Olavarria. Departamento de Electromecanica. Grupo Intelymec; Argentina;Fil: Sousa, André L.. Universidad de Las Islas Baleares. Departamento de Fisica; España;Fil: Rozenfeld, Alejandro Fabian. Universidad de Las Islas Baleares. Departamento de Fisica; España; Universidad Nacional del Centro de la Provincia de Bs.as.. Facultad de Ingenieria Olavarria. Departamento de Electromecanica. Grupo Intelymec; Argentina;In-teh2013-08info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/1135Villar, Sebastian Aldo; Acosta, Gerardo Gabriel; Sousa, André L.; Rozenfeld, Alejandro Fabian; Evaluation of an efficient approach for target tracking from acoustic imagery for the perception system of an autonomous underwater vehicle; In-teh; International Journal Of Advanced Robotic Systems; 11; 8-2013; 1-131729-88061729-8814enginfo:eu-repo/semantics/altIdentifier/doi/10.5772/56954info:eu-repo/semantics/altIdentifier/url/http://cdn.intechopen.com/pdfs-wm/46265.pdfinfo:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-15T14:51:33Zoai:ri.conicet.gov.ar:11336/1135instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-10-15 14:51:33.552CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Evaluation of an efficient approach for target tracking from acoustic imagery for the perception system of an autonomous underwater vehicle
title Evaluation of an efficient approach for target tracking from acoustic imagery for the perception system of an autonomous underwater vehicle
spellingShingle Evaluation of an efficient approach for target tracking from acoustic imagery for the perception system of an autonomous underwater vehicle
Villar, Sebastian Aldo
CA-CFAR
SIDE-SCAN SONAR
AUTOMATIC OBJETIVE DETECTION
SONAR IMAGERY
AUV
title_short Evaluation of an efficient approach for target tracking from acoustic imagery for the perception system of an autonomous underwater vehicle
title_full Evaluation of an efficient approach for target tracking from acoustic imagery for the perception system of an autonomous underwater vehicle
title_fullStr Evaluation of an efficient approach for target tracking from acoustic imagery for the perception system of an autonomous underwater vehicle
title_full_unstemmed Evaluation of an efficient approach for target tracking from acoustic imagery for the perception system of an autonomous underwater vehicle
title_sort Evaluation of an efficient approach for target tracking from acoustic imagery for the perception system of an autonomous underwater vehicle
dc.creator.none.fl_str_mv Villar, Sebastian Aldo
Acosta, Gerardo Gabriel
Sousa, André L.
Rozenfeld, Alejandro Fabian
author Villar, Sebastian Aldo
author_facet Villar, Sebastian Aldo
Acosta, Gerardo Gabriel
Sousa, André L.
Rozenfeld, Alejandro Fabian
author_role author
author2 Acosta, Gerardo Gabriel
Sousa, André L.
Rozenfeld, Alejandro Fabian
author2_role author
author
author
dc.subject.none.fl_str_mv CA-CFAR
SIDE-SCAN SONAR
AUTOMATIC OBJETIVE DETECTION
SONAR IMAGERY
AUV
topic CA-CFAR
SIDE-SCAN SONAR
AUTOMATIC OBJETIVE DETECTION
SONAR IMAGERY
AUV
purl_subject.fl_str_mv https://purl.org/becyt/ford/2.2
https://purl.org/becyt/ford/2
dc.description.none.fl_txt_mv This article describes the core algorithms of the perception system to be included within an autonomous underwater vehicle (AUV). This perception system is based on the acoustic data acquired from a side scan sonar (SSS). These data should be processed in an efficient time, so as to the perception system could detect and recognize a predefined target. This detection and recognition outcome is then an important piece of knowledge for the AUV's dynamic mission planner (DMP). Effectively, the DMP should propose different trajectories, navigation depths and other parameters that will change the robot's behavior, according to the perception system output. Hence, the time to make a decision is critical to assure safe robot operation and to acquire good quality data, and consequently the efficiency of the on-line image processing from acoustic data, is a key issue. Current techniques for acoustic data processing are time and computationally intensive. Hence, it was decided to process data coming from a SSS using a technique that is used for radars, due to its efficiency and its amenability to on-line processing. The engineering problem to solve in this case, is underwater pipeline tracking for routinely inspections in the off-shore industry. Then, an automatic oil pipeline detection system was developed borrowing techniques from processing of radar measurements. The radar technique is known as Cell Average-Constant False Alarm Rate (CA-CFAR). With a slight variation of the algorithms underlying this radar technique, consisting of the previous accumulation of partial sums, a great improvement in computing time and effort is achieved. Finally, a comparison with previous approaches over images acquired with a SSS from a vessel in the Salvador de Bahia bay in Brazil, showed the feasibility of using this on-board technique for AUV perception.
Fil: Villar, Sebastian Aldo. Universidad Nacional del Centro de la Provincia de Bs.as.. Facultad de Ingenieria Olavarria. Departamento de Electromecanica. Grupo Intelymec; Argentina; Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina;
Fil: Acosta, Gerardo Gabriel. Universidad de Las Islas Baleares. Departamento de Fisica; España; Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ingenieria Olavarria. Departamento de Electromecanica. Grupo Intelymec; Argentina;
Fil: Sousa, André L.. Universidad de Las Islas Baleares. Departamento de Fisica; España;
Fil: Rozenfeld, Alejandro Fabian. Universidad de Las Islas Baleares. Departamento de Fisica; España; Universidad Nacional del Centro de la Provincia de Bs.as.. Facultad de Ingenieria Olavarria. Departamento de Electromecanica. Grupo Intelymec; Argentina;
description This article describes the core algorithms of the perception system to be included within an autonomous underwater vehicle (AUV). This perception system is based on the acoustic data acquired from a side scan sonar (SSS). These data should be processed in an efficient time, so as to the perception system could detect and recognize a predefined target. This detection and recognition outcome is then an important piece of knowledge for the AUV's dynamic mission planner (DMP). Effectively, the DMP should propose different trajectories, navigation depths and other parameters that will change the robot's behavior, according to the perception system output. Hence, the time to make a decision is critical to assure safe robot operation and to acquire good quality data, and consequently the efficiency of the on-line image processing from acoustic data, is a key issue. Current techniques for acoustic data processing are time and computationally intensive. Hence, it was decided to process data coming from a SSS using a technique that is used for radars, due to its efficiency and its amenability to on-line processing. The engineering problem to solve in this case, is underwater pipeline tracking for routinely inspections in the off-shore industry. Then, an automatic oil pipeline detection system was developed borrowing techniques from processing of radar measurements. The radar technique is known as Cell Average-Constant False Alarm Rate (CA-CFAR). With a slight variation of the algorithms underlying this radar technique, consisting of the previous accumulation of partial sums, a great improvement in computing time and effort is achieved. Finally, a comparison with previous approaches over images acquired with a SSS from a vessel in the Salvador de Bahia bay in Brazil, showed the feasibility of using this on-board technique for AUV perception.
publishDate 2013
dc.date.none.fl_str_mv 2013-08
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/1135
Villar, Sebastian Aldo; Acosta, Gerardo Gabriel; Sousa, André L.; Rozenfeld, Alejandro Fabian; Evaluation of an efficient approach for target tracking from acoustic imagery for the perception system of an autonomous underwater vehicle; In-teh; International Journal Of Advanced Robotic Systems; 11; 8-2013; 1-13
1729-8806
1729-8814
url http://hdl.handle.net/11336/1135
identifier_str_mv Villar, Sebastian Aldo; Acosta, Gerardo Gabriel; Sousa, André L.; Rozenfeld, Alejandro Fabian; Evaluation of an efficient approach for target tracking from acoustic imagery for the perception system of an autonomous underwater vehicle; In-teh; International Journal Of Advanced Robotic Systems; 11; 8-2013; 1-13
1729-8806
1729-8814
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.5772/56954
info:eu-repo/semantics/altIdentifier/url/http://cdn.intechopen.com/pdfs-wm/46265.pdf
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv In-teh
publisher.none.fl_str_mv In-teh
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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