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    <identifier>10.57760/sciencedb.30393</identifier>
    <datestamp>2025-10-24T14:48:28Z</datestamp>
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  <dc:date>2025-10-24</dc:date>
  <dc:title>NeuralSymbolic SLAM Cognitive Architecture Autonomous Navigation Complex Environments</dc:title>
  <dc:identifier>doi:10.57760/sciencedb.30393</dc:identifier>
  <dc:language>en</dc:language>
  <dc:description>This dataset is derived from the research of ' NeuralSymbolic SLAM Cognitive Architecture Autonomous Navigation Complex Environments '. It contains 1200 sets of real indoor and simulated environment samples, covering four typical navigation environments : hospital corridors, intelligent warehouses, outdoor scenes and large shopping malls. The&amp;nbsp;data is synchronously collected by RGB-D camera and 2D laser radar, and provides pixel-level 50-class target semantic annotation, logical relationship label and corresponding navigation decision record, which is used to support the perception, reasoning and decision-making algorithm verification of neural-symbol fusion SLAM system in dynamic semantic scene.</dc:description>
  <dc:subject>Neural Symbols; Simultaneous Localization and Mapping; Symbolic Reasoning; Human Cognitive Model; Autonomous Navigation</dc:subject>
  <dc:creator>Feng Xiao</dc:creator>
  <dc:creator>Shiwei Chu</dc:creator>
  <dc:creator>Jun Xie</dc:creator>
  <dc:creator>Youhai Zhang</dc:creator>
  <dc:creator>Xing Guo</dc:creator>
  <dc:rights>PUBLIC</dc:rights>
  <dc:rights>https://creativecommons.org/licenses/by-nc/4.0/</dc:rights>
  <dc:type>dataset</dc:type>
  <dc:publisher>Science Data Bank</dc:publisher>
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