DocumentCode :
250658
Title :
A statistical measure for map consistency in SLAM
Author :
Mazuran, Mladen ; Diego Tipaldi, Gian ; Spinello, Luciano ; Burgard, Wolfram ; Stachniss, Cyrill
Author_Institution :
Inst. of Comput. Sci., Univ. of Freiburg, Freiburg, Germany
fYear :
2014
fDate :
May 31 2014-June 7 2014
Firstpage :
3650
Lastpage :
3655
Abstract :
Map consistency is an important requirement for applications in which mobile robots need to effectively perform autonomous navigation tasks. While recent SLAM techniques provide an increased robustness even in the context of bad initializations or data association outliers, the question of how to determine whether or not the resulting map is consistent is still an open problem. In this paper, we introduce a novel measure for map consistency. We compute this measure by taking into account the discrepancies in the sensor data and leverage it to address two important problems in SLAM. First, we derive a statistical test for assessing whether a map is consistent or not. Second, we employ it to automatically set the free parameter of dynamic covariance scaling, a robust SLAM back-end. We present an evaluation of our approach on over 50 maps sourced from 16 publicly available datasets and illustrate its capability for the inconsistency detection and the tuning of the parameter of the back-end.
Keywords :
SLAM (robots); mobile robots; path planning; statistical testing; autonomous navigation task; dynamic covariance scaling; map consistency; mobile robot; robust SLAM back-end; statistical measure; statistical testing; Measurement by laser beam; Optimization; Robustness; Silicon; Simultaneous localization and mapping; Tuning;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Robotics and Automation (ICRA), 2014 IEEE International Conference on
Conference_Location :
Hong Kong
Type :
conf
DOI :
10.1109/ICRA.2014.6907387
Filename :
6907387
Link To Document :
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