Publication:
Into the dirt: Datasets of sewer networks with aerial and ground platforms

dc.contributor.authorAlejo Teissière, David
dc.contributor.authorFrançois Chataigner,
dc.contributor.authorDaniel Serrano,
dc.contributor.authorMerino, Luis
dc.contributor.authorCaballero, Fernando
dc.date.accessioned2026-01-20T11:24:27Z
dc.date.available2026-01-20T11:24:27Z
dc.date.issued2021
dc.descriptionMinisterio de Ciencia, Innovación y Universidades. Grant Number: RTI2018-100847-B-C22 Agència per a la Competitivitat de l'Empresa FP7 Information and Communication Technologies. Grant Number: 601116 Ministerio de Ciencia e Innovación. Grant Number: FJCI-2015-25700
dc.description.abstractThis paper presents an unprecedented set of data in a challenging undergroundenvironment: the visitable sewers of Barcelona. To the best of our knowledge, this isthe first data set involving ground and aerial robots in such scenario: the sewerinspection autonomous robot (SIAR) ground robot and the autonomous robot forsewer inspection aerial platform. These platforms captured data from a great varietyof sensors, including sequences of red green blue‐depth (RGB‐D) images with theironboard cameras. The set consists of 14 logs of experiments that were obtained inmore than 10 different days and in four different locations. The complete length ofthe experiments in the data set exceeds 5 km. In addition, we provide the users witha partial ground‐truth and baselines of the localization of the platforms, which canbe used for testing their localization and simultaneous localization and mapping(SLAM) algorithms. We also provide details on the setup and execution of eachmission and a partial labeling of the elements found in the sewers. All the data wererecorded by using the rosbag tool from robot operating system framework. Our goalis to make the data available to the scientific community as a benchmark to testlocalization, SLAM and classification algorithms in underground environments. Thedata set are available at https://robotics.upo.es/datasets/echord.
dc.description.sponsorshipUniversidad Pablo de Olavide. Departamento de Deporte e informática
dc.format.mimetypeapplication/pdf
dc.identifier.citationAlejo D, Chataigner F, Serrano D, Merino L, Caballero F. Into the dirt: Datasets of sewer networks with aerial and ground platforms. J Field Robotics. 2021; 38: 105–120. https://doi.org/10.1002/rob.21976
dc.identifier.doi10.1002/rob.21976
dc.identifier.urihttps://hdl.handle.net/10433/25692
dc.language.isoen
dc.publisherWiley
dc.relation.projectIDinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RTI2018-100847-B-C22/ES/PLANIFICACION, PERCEPCION Y NAVEGACION COOPERATIVAS EN SISTEMAS DE UAVS EN COORDINACION CON UGV/
dc.relation.projectIDinfo:eu-repo/grantAgreement/EC/FP7/601116/EU
dc.relation.projectIDinfo:eu-repo/grantAgreement/MINECO//FJCI-2015-25700/ES/FJCI-2015-25700/
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internationalen
dc.rights.accessRightsopen access
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectField robotics
dc.subjectSewer inspection
dc.titleInto the dirt: Datasets of sewer networks with aerial and ground platforms
dc.typejournal article
dc.type.hasVersionAM
dspace.entity.typePublication
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relation.isAuthorOfPublication021f43bc-c25f-40dd-9ac1-0fc2933e7071
relation.isAuthorOfPublication144853bd-af99-4072-840b-71bdd0b94309
relation.isAuthorOfPublication.latestForDiscoverye2353d36-ad4d-4a5a-a727-20ba4d68f2ab

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