Title :
Localization in highly dynamic environments using dual-timescale NDT-MCL
Author :
Valencia, Rafael ; Saarinen, Jari ; Andreasson, Henrik ; Vallve, Joan ; Andrade-Cetto, Juan ; Lilienthal, Achim J.
Author_Institution :
Center of Appl. Autonomous Sensor Syst. (AASS), Orebro Univ., Orebro, Sweden
fDate :
May 31 2014-June 7 2014
Abstract :
Industrial 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 proposed 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.
Keywords :
Monte Carlo methods; SLAM (robots); automatic guided vehicles; industrial robots; mobile robots; normal distribution; particle filtering (numerical methods); path planning; transforms; automatically guided vehicles; dual-timescale NDT-MCL; dual-timescale normal distributions transform Monte Carlo localization; industrial environments; infrastructure free localization systems; logistics application scenarios; material transfer flow; mobile robotic systems; normal distributions transform occupancy maps; particle filter based localization method; short-term map; static map; Accuracy; Atmospheric measurements; Gaussian distribution; Heuristic algorithms; Particle measurements; Transforms; Vehicle dynamics;
Conference_Titel :
Robotics and Automation (ICRA), 2014 IEEE International Conference on
Conference_Location :
Hong Kong
DOI :
10.1109/ICRA.2014.6907433