DocumentCode :
679329
Title :
Probabilistic approach to self-localization for autonomous mobile outdoor robotics based on hybrid map knowledge
Author :
Kuhnert, Lars ; Meier, Benjamin ; Kuhnert, Klaus-Dieter
Author_Institution :
Inst. of Real-time Learning Syst., Univ. of Siegen, Siegen, Germany
fYear :
2013
fDate :
6-9 Oct. 2013
Firstpage :
1791
Lastpage :
1798
Abstract :
We propose a probabilistic approach to self-localization of an autonomous mobile outdoor robot based on hybrid (metrically-annotated topological) map knowledge. A particle filter is used to estimate the state of the robot based on map data and relative dead-reckoning measurements. Convergence speed of the filter is improved by equidistant road sampling placing particles equidistantly along map segments. We introduce a novel particle weighting technique which realizes a comparison of a local vehicle motion buffer to local map data to increase the robustness of the estimation process by significantly reducing the occurrence of ambiguous situations during the localization process. The weighting technique is combined with a custom resampling method generating an increased attachment of particles to nearby road segments. We present experimental results of long-distance test runs featuring various difficult local map configurations demonstrating the robustness and quality of the proposed algorithm even in presence of map errors.
Keywords :
mobile robots; motion control; particle filtering (numerical methods); probability; robust control; ambiguous situations; autonomous mobile outdoor robotics; custom resampling method; equidistant road sampling; estimation process robustness; filter convergence speed; hybrid map knowledge; local map configurations; local vehicle motion buffer; long-distance test runs; map data; map errors; particle filter; probabilistic approach; relative dead-reckoning measurements; self-localization; Accuracy; Equations; Land vehicles; Mathematical model; Probabilistic logic; Robots; Robustness;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Transportation Systems - (ITSC), 2013 16th International IEEE Conference on
Conference_Location :
The Hague
Type :
conf
DOI :
10.1109/ITSC.2013.6728488
Filename :
6728488
Link To Document :
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