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  • 标题:Scalable Robot Localization Using Incremental Map-Matching Techniques
  • 本地全文:下载
  • 作者:Takeshi UEDA ; Kanji TANAKA
  • 期刊名称:Journal of Computational Science and Technology
  • 电子版ISSN:1881-6894
  • 出版年度:2010
  • 卷号:4
  • 期号:1
  • 页码:1-10
  • DOI:10.1299/jcst.4.1
  • 出版社:The Japan Society of Mechanical Engineers
  • 摘要:Map-matching is an effective approach for robot localization using large-size landmark maps. Existing map-matching techniques typically address batch localization applications where the objective maps are given prior to the map-matching task. In contrast to the existing techniques, this paper addresses real-time localization applications where the maps can be incrementally updated even during the map-matching task. We present a solution that combines an incremental RANSAC map-matching with an ANN landmark database. Experiments using real data show promising results.
  • 关键词:Mobile Robot;Robot Localization;Map Matching
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