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dc.contributor.authorValencia Carreño, Rafael
dc.contributor.authorSaarinen, Jari
dc.contributor.authorAndreasson, Henrik
dc.contributor.authorVallvé Navarro, Joan
dc.contributor.authorAndrade-Cetto, Juan
dc.contributor.authorLilienthal, Achim
dc.contributor.otherInstitut de Robòtica i Informàtica Industrial
dc.date.accessioned2015-07-13T10:29:31Z
dc.date.available2015-07-13T10:29:31Z
dc.date.created2014
dc.date.issued2014
dc.identifier.citationValencia, R. [et al.]. Localization in highly dynamic environments using dual-timescale NDT-MCL. A: IEEE International Conference on Robotics and Automation. "2014 IEEE International Conference on Robotics and Automation (ICRA)". Hong Kong: Institute of Electrical and Electronics Engineers (IEEE), 2014, p. 3956-3962.
dc.identifier.urihttp://hdl.handle.net/2117/28567
dc.description.abstractIndustrial environments are rarely static and often their configuration is continuously changing due to the material transfer flow. This is a major challenge for infrastructure free localization systems. In this paper we address this challenge by introducing a localization approach that uses a dual- timescale approach. The proposed approach - Dual-Timescale Normal Distributions Transform Monte Carlo Localization (DT- NDT-MCL) - is a particle filter based localization method, which simultaneously keeps track of the pose using an apriori known static map and a short-term map. The short-term map is continuously updated and uses Normal Distributions Transform Occupancy maps to maintain the current state of the environment. A key novelty of this approach is that it does not have to select an entire timescale map but rather use the best timescale locally. The approach has real-time performance and is evaluated using three datasets with increasing levels of dynamics. We compare our approach against previously pro- posed NDT-MCL and commonly used SLAM algorithms and show that DT-NDT-MCL outperforms competing algorithms with regards to accuracy in all three test cases.
dc.format.extent7 p.
dc.language.isoeng
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Spain
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subjectÀrees temàtiques de la UPC::Informàtica::Robòtica
dc.subject.otherrobots
dc.titleLocalization in highly dynamic environments using dual-timescale NDT-MCL
dc.typeConference report
dc.contributor.groupUniversitat Politècnica de Catalunya. VIS - Visió Artificial i Sistemes Intel·ligents
dc.identifier.doi10.1109/ICRA.2014.6907433
dc.subject.inspecClassificació INSPEC::Automation::Robots
dc.relation.publisherversionhttp://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6907433
dc.rights.accessOpen Access
local.identifier.drac15270334
dc.description.versionPostprint (author’s final draft)
dc.relation.projectidinfo:eu-repo/grantAgreement/EC/FP7/605598/EU/Cargo handling by Automated Next generation Transportation Systems for ports and terminals/CARGO-ANTS
dc.relation.projectidinfo:eu-repo/grantAgreement/EC/FP7/600877/EU/Social situation-aware perception and action for cognitive robots/SPENCER
local.citation.authorValencia, R.; Saarinen, J.; Andreasson, H.; Vallve, J.; Andrade-Cetto, J.; Lilienthal, A.
local.citation.contributorIEEE International Conference on Robotics and Automation
local.citation.pubplaceHong Kong
local.citation.publicationName2014 IEEE International Conference on Robotics and Automation (ICRA)
local.citation.startingPage3956
local.citation.endingPage3962


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