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Smartphone-Based Indoor Visual Navigation with Leader-Follower Mode

机译:基于智能手机的室内视觉导航,带有领导跟随器模式

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摘要

Existing indoor navigation solutions usually require pre-deployed comprehensive location services with precise indoor maps and, more importantly, all rely on dedicatedly installed or existing infrastructure. In this article, we present Pair-Navi, an infrastructure-free indoor navigation system that circumvents all these requirements by reusing a previous traveler's (i.e., leader) trace experience to navigate future users (i.e., followers) in a Peer-to-Peer mode. Our system leverages the advances of visual simultaneous localization and mapping (SLAM) on commercial smartphones. Visual SLAM systems, however, are vulnerable to environmental dynamics in the precision and robustness and involve intensive computation that prohibits real-time applications. To combat environmental changes, we propose to cull non-rigid contexts and keep only the static and rigid contents in use. To enable real-time navigation on mobiles, we decouple and reorganize the highly coupled SLAM modules for leaders and followers. We implement Pair-Navi on commodity smartphones and validate its performance in three diverse buildings and two standard datasets (FUM and KITTI). Our results show that Pair-Navi achieves an immediate navigation success rate of 98.6%, which maintains as 83.4% even after 2 weeks since the leaders' traces were collected, outperforming the state-of-the-art solutions by 50%. Being truly infrastructure-free, Pair-Navi sheds lights on practical indoor navigations for mobile users.
机译:现有的室内导航解决方案通常需要预先部署的全面位置服务,具有精确的室内地图,更重要的是所有依赖于义务安装或现有的基础架构。在本文中,我们呈现BaiR-Navi,这是一种无基础设施的室内导航系统,通过重用以前的旅行者(即,领导者)跟踪体验来导航在对等体中导航的未来用户(即追随者)来缩短所有这些要求模式。我们的系统利用了在商业智能手机上的视觉同步定位和映射(SLAM)的进展。然而,视觉SLAM系统易受精确和鲁棒性的环境动态,并涉及禁止实时应用的强化计算。为了打击环境变化,我们建议剔除非刚性上下文,只能保持使用的静态和刚性内容。为了在移动手机上进行实时导航,我们将与领导和粉丝的高度耦合的SLAM模块进行解耦并重新组织。我们在商品智能手机上实施Bia-Navi,并在三个不同建筑物和两个标准数据集(FUM和Kitti)中验证其性能。我们的结果表明,一对NAVI实现了98.6%的直接导航成功率,即使收集领导痕迹,且优于最先进的解决方案,即使在2周后,也保持了83.4%。作为无基础架构,对Navi Sheds为移动用户的实际室内导航而亮起。

著录项

  • 来源
    《ACM transactions on sensor networks》 |2021年第2期|18.1-18.22|共22页
  • 作者单位

    Tsinghua Univ Sch Software 30 Shuangqing Rd Beijing 100084 Peoples R China|Tsinghua Univ BNRist 30 Shuangqing Rd Beijing 100084 Peoples R China;

    Tsinghua Univ Sch Software 30 Shuangqing Rd Beijing 100084 Peoples R China|Tsinghua Univ BNRist 30 Shuangqing Rd Beijing 100084 Peoples R China;

    Tsinghua Univ Sch Software 30 Shuangqing Rd Beijing 100084 Peoples R China|Tsinghua Univ BNRist 30 Shuangqing Rd Beijing 100084 Peoples R China;

    Univ Maryland Dept Elect & Comp Engn Washington DC 20742 USA;

    Tsinghua Univ Sch Software 30 Shuangqing Rd Beijing 100084 Peoples R China|Tsinghua Univ BNRist 30 Shuangqing Rd Beijing 100084 Peoples R China;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Indoor navigation; computer vision; visual SLAM;

    机译:室内导航;电脑视觉;视觉猛击;

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