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  • 标题:Workload Partitioning of a Bio-inspired Simultaneous Localization and Mapping Algorithm on an Embedded Architecture
  • 本地全文:下载
  • 作者:Amraoui Mounir ; Latif Rachid ; Abdelhafid El Ouardi
  • 期刊名称:International Journal of Advanced Computer Science and Applications(IJACSA)
  • 印刷版ISSN:2158-107X
  • 电子版ISSN:2156-5570
  • 出版年度:2021
  • 卷号:12
  • 期号:5
  • 页码:221-229
  • DOI:10.14569/IJACSA.2021.0120528
  • 出版社:Science and Information Society (SAI)
  • 摘要:Many algorithms were developed to perform visual localization and mapping (SLAM) for robotic applications. These algorithms used monocular or stereovision systems to solve constraints related to the navigation in unknown or dynamic environment. The requirement of SLAM systems in terms of processing time and precision is a factor that limits their use in many embedded applications like UAVs or autonomous vehicles. Meanwhile, trends towards low-cost and low-power processing require massive parallelism on hardware architectures. The emergence of recent heterogeneous embedded architectures should help design embedded systems dedicated to Visual SLAM applications. It was demonstrated in a previous work that bio-inspired algorithms are competitive compared to classical methods based on image processing and environment perception. This paper is a study of a bio-inspired SLAM algorithm with the aim of making it suitable for an implementation on a heterogeneous architecture dedicated for embedded applications. An algorithm-architecture adequation approach is used to achieve a workload partitioning on CPU-GPU architecture and hence speeding up processing tasks.
  • 关键词:Simultaneous localization and mapping (SLAM); Bio-inspired algorithms; CPU-GPU workload partitioning; embedded systems; visual acuity (VA); hardware/software codesign
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