dc.creator | Alejo, David | es |
dc.creator | Caballero Benítez, Fernando | es |
dc.creator | Merino, Luis | es |
dc.date.accessioned | 2020-02-14T18:38:56Z | |
dc.date.available | 2020-02-14T18:38:56Z | |
dc.date.issued | 2019-11 | |
dc.identifier.citation | Alejo, D., Caballero Benítez, F. y Merino, L. (2019). A Robust Localization System for Inspection Robots in Sewer Networks †. Sensors, 19 (22). Article number 4946. | |
dc.identifier.issn | 1424-8220 | es |
dc.identifier.uri | https://hdl.handle.net/11441/93224 | |
dc.description.abstract | Sewers represent a very important infrastructure of cities whose state should be monitored
periodically. However, the length of such infrastructure prevents sensor networks from being
applicable. In this paper, we present a mobile platform (SIAR) designed to inspect the sewer network.
It is capable of sensing gas concentrations and detecting failures in the network such as cracks and
holes in the floor and walls or zones were the water is not flowing. These alarms should be precisely
geo-localized to allow the operators performing the required correcting measures. To this end, this
paper presents a robust localization system for global pose estimation on sewers. It makes use of prior
information of the sewer network, including its topology, the different cross sections traversed and
the position of some elements such as manholes. The system is based on a Monte Carlo Localization
system that fuses wheel and RGB-D odometry for the prediction stage. The update step takes into
account the sewer network topology for discarding wrong hypotheses. Additionally, the localization
is further refined with novel updating steps proposed in this paper which are activated whenever
a discrete element in the sewer network is detected or the relative orientation of the robot over the
sewer gallery could be estimated. Each part of the system has been validated with real data obtained
from the sewers of Barcelona. The whole system is able to obtain median localization errors in the
order of one meter in all cases. Finally, the paper also includes comparisons with state-of-the-art
Simultaneous Localization and Mapping (SLAM) systems that demonstrate the convenience of the
approach. | es |
dc.description.sponsorship | Unión Europea ECHORD ++ 601116 | es |
dc.description.sponsorship | Ministerio de Ciencia, Innovación y Universidades de España RTI2018-100847-B-C22 | es |
dc.format | application/pdf | es |
dc.language.iso | eng | es |
dc.publisher | MDPI | es |
dc.relation.ispartof | Sensors, 19 (22). Article number 4946. | |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.subject | Localization | es |
dc.subject | Sewer network | es |
dc.subject | Field robotics | es |
dc.subject | Monte Carlo Localization | es |
dc.subject | GPS-denied | es |
dc.subject | Underground robotics | es |
dc.subject | Global pose estimation | es |
dc.title | A Robust Localization System for Inspection Robots in Sewer Networks † | es |
dc.type | info:eu-repo/semantics/article | es |
dcterms.identifier | https://ror.org/03yxnpp24 | |
dc.type.version | info:eu-repo/semantics/publishedVersion | es |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | es |
dc.contributor.affiliation | Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática | es |
dc.relation.projectID | ECHORD ++ 601116 | es |
dc.relation.projectID | RTI2018-100847-B-C22 | es |
dc.relation.publisherversion | https://doi.org/10.3390/s19224946 | es |
dc.identifier.doi | 10.3390/s19224946 | es |
idus.format.extent | 28 p. | es |
dc.journaltitle | Sensors | es |
dc.publication.volumen | 19 | es |
dc.publication.issue | 22 | es |
dc.publication.endPage | Article number 4946 | es |