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文章基本信息

  • 标题:Robot Localization under Dynamic Uncertainty
  • 本地全文:下载
  • 作者:Bartkevičius ; Urniežius ; Žebrauskas
  • 期刊名称:Studies About Languages
  • 印刷版ISSN:2029-7203
  • 出版年度:2015
  • 卷号:95
  • 期号:7
  • 页码:3-6
  • DOI:10.5755/j01.eee.95.7.9981
  • 语种:English
  • 出版社:Faculty of Humanities, Kaunas University of Technology
  • 其他摘要:Maximum relative entropy approach for determination of robot localization principles is developed and confirmed through simulation experiments. The approach updates probability posterior using simultaneous updating of model combination and data. Model combination is performed using simultaneous validation and estimation of observed data. This approach is not restricted to robot localization tasks, but it can be used in a wide range of fields, including econometrics, physics and other technological sciences. This approach can be used in high volume real time systems, including signal analysis. Ill. 2, bibl. 5 (in English; summaries in English, Russian and Lithuanian).
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