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Journal Article Sonar Map Construction for Autonomous Mobile Robots Using a Data Association Filter
Cited 13 time in scopus Share share facebook twitter linkedin kakaostory
Authors
Yu-Cheol Lee, Jong Hwan Lim, Dong-Woo Cho, Wan Kyun Chung
Issue Date
2009-01
Citation
Advanced Robotics, v.23, no.1-2, pp.185-201
ISSN
0169-1864
Publisher
Taylor and Francis
Language
English
Type
Journal Article
DOI
https://dx.doi.org/10.1163/156855308X392735
Abstract
This paper presents a method for building a probability grid map for autonomous mobile robots with ultrasonic sensors using a data association filter (DAF). The method is based on evaluating the possibility that the acquired sonar data are all reflected by the same object. The DAF is able to associate data points with each other. Data affected by specular reflection are not likely to be associated with the same object, so they are excluded from the data cluster by the DAF, thereby improving the reliability of the data used for the probability grid map. Since the corrupted data are not used to update the probability map, it is possible to build a good quality grid map even in a specular environment. The DAF was applied to the Bayesian and the Orientation probability models, which are typical models used to build grid maps, to verify its effectiveness. Experimental results were also obtained using a mobile robot in a real-world environment. © 2009 VSP.
KSP Keywords
Autonomous mobile robots, Data association, Data cluster, Grid Map, Map Construction, Probability Model, Real-world, Specular Environment, probability map, specular reflection, ultrasonic sensor