Perception sensor integration for improved environmental reconstruction in quadruped robotics

Perception systems are fundamental in outdoor robotics, as their correct functionality is essential for tasks such as terrain identification, localization, navigation, and analysis of objects of interest. This is particularly relevant in search and rescue (SAR) robotics, where one current research f...

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Detalles Bibliográficos
Autores: Cruz Ulloa, Christyan, Del Cerro, Jaime, Barrientos, Antonio
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2024
País:España
Institución:Consejo Superior de Investigaciones Científicas (CSIC)
Repositorio:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/424429
Acceso en línea:http://hdl.handle.net/10261/424429
Access Level:acceso abierto
Palabra clave:Perception and sensing
Mobile robots
field robotic
Sensor integration and perception
Map building
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spelling Perception sensor integration for improved environmental reconstruction in quadruped roboticsCruz Ulloa, ChristyanDel Cerro, JaimeBarrientos, AntonioPerception and sensingMobile robotsfield roboticSensor integration and perceptionMap buildingPerception systems are fundamental in outdoor robotics, as their correct functionality is essential for tasks such as terrain identification, localization, navigation, and analysis of objects of interest. This is particularly relevant in search and rescue (SAR) robotics, where one current research focuses on the mobility and traversal of unstructured terrains (commonly resulting from natural disasters or attacks) using quadruped robots. 3D sensory systems, such as those based on 360-degree LiDAR, tend to create dead zones within a considerable radius relative to their placement (typically on the upper part of the robot), leaving the locomotion system without terrain information in those areas. This paper addresses the problem of eliminating these dead zones in the robot’s direction of movement during the process of environment reconstruction using point clouds. To achieve this, a ROS-based method has been implemented to integrate ”n” point clouds from different sensory sources into a single point cloud.This research has been possible thanks to the financing of “Proyecto CollaborativE Search And Rescue robots (CESAR)” (PID2022-142129OB-I00) founded by MCIN/AEI/ 10.13039/501100011033 and “ERDF A way of making Europe”.Peer reviewedComité Español de AutomáticaMinisterio de Ciencia e Innovación (España)Agencia Estatal de Investigación (España)Cruz Ulloa, Christyan [0000-0003-2824-6611]Del Cerro, Jaime [ 0000-0003-4893-2571]Barrientos, Antonio [0000-0003-1691-3907]Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]202620262024info:eu-repo/semantics/articlehttp://purl.org/coar/resource_type/c_6501Publisher's versioninfo:eu-repo/semantics/publishedVersionhttp://hdl.handle.net/10261/424429reponame:DIGITAL.CSIC. Repositorio Institucional del CSICinstname:Consejo Superior de Investigaciones Científicas (CSIC)Inglés#PLACEHOLDER_PARENT_METADATA_VALUE#info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/PID2022-142129OB-I00https://doi.org/10.17979/ja-cea.2024.45.10830Síinfo:eu-repo/semantics/openAccessoai:digital.csic.es:10261/4244292026-05-22T06:33:51Z
dc.title.none.fl_str_mv Perception sensor integration for improved environmental reconstruction in quadruped robotics
title Perception sensor integration for improved environmental reconstruction in quadruped robotics
spellingShingle Perception sensor integration for improved environmental reconstruction in quadruped robotics
Cruz Ulloa, Christyan
Perception and sensing
Mobile robots
field robotic
Sensor integration and perception
Map building
title_short Perception sensor integration for improved environmental reconstruction in quadruped robotics
title_full Perception sensor integration for improved environmental reconstruction in quadruped robotics
title_fullStr Perception sensor integration for improved environmental reconstruction in quadruped robotics
title_full_unstemmed Perception sensor integration for improved environmental reconstruction in quadruped robotics
title_sort Perception sensor integration for improved environmental reconstruction in quadruped robotics
dc.creator.none.fl_str_mv Cruz Ulloa, Christyan
Del Cerro, Jaime
Barrientos, Antonio
author Cruz Ulloa, Christyan
author_facet Cruz Ulloa, Christyan
Del Cerro, Jaime
Barrientos, Antonio
author_role author
author2 Del Cerro, Jaime
Barrientos, Antonio
author2_role author
author
dc.contributor.none.fl_str_mv Ministerio de Ciencia e Innovación (España)
Agencia Estatal de Investigación (España)
Cruz Ulloa, Christyan [0000-0003-2824-6611]
Del Cerro, Jaime [ 0000-0003-4893-2571]
Barrientos, Antonio [0000-0003-1691-3907]
Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]
dc.subject.none.fl_str_mv Perception and sensing
Mobile robots
field robotic
Sensor integration and perception
Map building
topic Perception and sensing
Mobile robots
field robotic
Sensor integration and perception
Map building
description Perception systems are fundamental in outdoor robotics, as their correct functionality is essential for tasks such as terrain identification, localization, navigation, and analysis of objects of interest. This is particularly relevant in search and rescue (SAR) robotics, where one current research focuses on the mobility and traversal of unstructured terrains (commonly resulting from natural disasters or attacks) using quadruped robots. 3D sensory systems, such as those based on 360-degree LiDAR, tend to create dead zones within a considerable radius relative to their placement (typically on the upper part of the robot), leaving the locomotion system without terrain information in those areas. This paper addresses the problem of eliminating these dead zones in the robot’s direction of movement during the process of environment reconstruction using point clouds. To achieve this, a ROS-based method has been implemented to integrate ”n” point clouds from different sensory sources into a single point cloud.
publishDate 2024
dc.date.none.fl_str_mv 2024
2026
2026
dc.type.none.fl_str_mv info:eu-repo/semantics/article
http://purl.org/coar/resource_type/c_6501
Publisher's version
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10261/424429
url http://hdl.handle.net/10261/424429
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv #PLACEHOLDER_PARENT_METADATA_VALUE#
info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/PID2022-142129OB-I00
https://doi.org/10.17979/ja-cea.2024.45.10830
Sí
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Comité Español de Automática
publisher.none.fl_str_mv Comité Español de Automática
dc.source.none.fl_str_mv reponame:DIGITAL.CSIC. Repositorio Institucional del CSIC
instname:Consejo Superior de Investigaciones Científicas (CSIC)
instname_str Consejo Superior de Investigaciones Científicas (CSIC)
reponame_str DIGITAL.CSIC. Repositorio Institucional del CSIC
collection DIGITAL.CSIC. Repositorio Institucional del CSIC
repository.name.fl_str_mv
repository.mail.fl_str_mv
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