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Localization in highly dynamic environments using dual-timescale NDT-MCL
Örebro University, School of Science and Technology. (AASS MRO Lab)
Örebro University, School of Science and Technology. (AASS MRO Lab)
Örebro University, School of Science and Technology. (AASS MRO Lab)ORCID iD: 0000-0002-2953-1564
CSIC-UPC, Barcelona,Spain.
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2014 (English)In: 2014 IEEE International Conference on Robotics and Automation (ICRA), IEEE Robotics and Automation Society, 2014, 3956-3962 p.Conference paper, Published paper (Refereed)
Abstract [en]

Industrial environments are rarely static and oftentheir configuration is continuously changing due to the materialtransfer flow. This is a major challenge for infrastructure freelocalization systems. In this paper we address this challengeby introducing a localization approach that uses a dualtimescaleapproach. The proposed approach - Dual-TimescaleNormal Distributions Transform Monte Carlo Localization (DTNDT-MCL) - is a particle filter based localization method,which simultaneously keeps track of the pose using an aprioriknown static map and a short-term map. The short-termmap is continuously updated and uses Normal DistributionsTransform Occupancy maps to maintain the current state ofthe environment. A key novelty of this approach is that it doesnot have to select an entire timescale map but rather use thebest timescale locally. The approach has real-time performanceand is evaluated using three datasets with increasing levels ofdynamics. We compare our approach against previously proposedNDT-MCL and commonly used SLAM algorithms andshow that DT-NDT-MCL outperforms competing algorithmswith regards to accuracy in all three test cases.

Place, publisher, year, edition, pages
IEEE Robotics and Automation Society, 2014. 3956-3962 p.
Series
Proceedings - IEEE International Conference on Robotics and Automation, ISSN 1050-4729
Keyword [en]
Localization, Monte Carlo Localization, Intra Logistics, Mapping
National Category
Computer Science
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:oru:diva-41234DOI: 10.1109/ICRA.2014.6907433ISI: 000377221103145Scopus ID: 2-s2.0-84929180176OAI: oai:DiVA.org:oru-41234DiVA: diva2:780074
Conference
IEEE International Conference on Robotics and Automation (ICRA), Hongkong, China, May 31 - June 7, 2014
Projects
FP7-ICT-600877 (SPENCER)
Funder
EU, FP7, Seventh Framework Programme
Available from: 2015-01-13 Created: 2015-01-13 Last updated: 2017-10-18Bibliographically approved

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Valencia, RafaelSaarinen, JariAndreasson, HenrikLilienthal, Achim J.
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