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Localization in highly dynamic environments using dual-timescale NDT-MCL

AutorValencia, Rafael; Saarinen, Jari; Andreasson, Henrik; Vallvé, Joan; Andrade-Cetto, Juan ; Lilienthal, Achim J.
Fecha de publicación2014
EditorInstitute of Electrical and Electronics Engineers
CitaciónIEEE International Conference on Robotics and Automation: 3596-3962 (2014)
ResumenIndustrial 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.
Versión del editorhttp://dx.doi.org/10.1109/ICRA.2014.6907433
Identificadoresissn: 1050-4729
Aparece en las colecciones: (IRII) Artículos
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