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
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/1135
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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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1846083041902985216 |
score |
12.891075 |