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  • 标题:A terrain segmentation method based on pyramid scene parsing-mobile network for outdoor robots
  • 本地全文:下载
  • 作者:Botao Zhang ; Tao Hong ; Rong Xiong
  • 期刊名称:International Journal of Advanced Robotic Systems
  • 印刷版ISSN:1729-8806
  • 电子版ISSN:1729-8814
  • 出版年度:2021
  • 卷号:18
  • 期号:5
  • DOI:10.1177/17298814211048633
  • 语种:English
  • 出版社:SAGE Publications
  • 摘要:Terrain segmentation is of great significance to robot navigation, cognition, and map building. However, the existing vision-based methods are challenging to meet the high-accuracy and real-time performance. A terrain segmentation method with a novel lightweight pyramid scene parsing mobile network is proposed for terrain segmentation in robot navigation. It combines the feature extraction structure of MobileNet and the encoding path of pyramid scene parsing network. The depthwise separable convolution, the spatial pyramid pooling, and the feature fusion are employed to reduce the onboard computing time of pyramid scene parsing mobile network. A unique data set called Hangzhou Dianzi University Terrain Dataset is constructed for terrain segmentation, which contains more than 4000 images from 10 different scenes. The data set was collected from a robot’s perspective to make it more suitable for robotic applications. Experimental results show that the proposed method has high-accuracy and real-time performance on the onboard computer. Moreover, its real-time performance is better than most state-of-the-art methods for terrain segmentation.
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