Bumping: A Bump-Aided Inertial Navigation Method for Indoor Vehicles Using Smartphones
Bumping: A Bump-Aided Inertial Navigation Method for Indoor Vehicles Using Smartphones
复制标题
碰撞：使用智能手机的室内车辆的碰撞辅助惯性导航方法
DOI：
10.1109/tpds.2013.194
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发表时间：
2014-07-01
影响因子：
5.3
通讯作者：
Wu, Jie
中科院分区：
文献类型：
--
作者：
Tan, Guang;Lu, Mingming;Wu, Jie
现代智能手机配备了加速度计和陀螺仪，为室内环境（例如停车场）中的车辆提供了一种吸引人的无基础设施导航方法。然而，基于智能手机的惯性导航系统（INS）面临两个严重的问题。首先，它会受到随着时间的推移而迅速积累的错误的影响，这些错误可能会增长到使导航变得毫无意义的程度。其次，在没有人类输入或外部参考的情况下，智能手机几乎无法推断其初始位置/速度，这是距离计算的基础，因为智能手机所能学习的只是其加速度。这引起了实际问题，因为用户通常需要在不确定其当前位置时精确地开始室内导航。在本文中，我们提出了碰撞，碰撞辅助惯性导航方法，显着简化了上述两个问题。该方法的核心是一个颠簸匹配算法，它利用现成的减速带的位置信息，为INS提供有用的参考。所提出的方法易于实现，不需要基础设施，并产生几乎为零的额外能量。我们在不同环境特征的树木停车库中进行了真实的实验。碰撞方法在这些情况下产生4-5米的平均位置误差，与基本惯性导航方法相比，精度提高了87.1%。
Equipped with accelerometers and gyroscopes, modern smartphones provide an appealing approach to infrastructure-free navigation for vehicles in indoor environments (for example parking garages). However, a smartphone-based inertial navigation system (INS) faces two serious problems. First, it is subject to errors that accumulate over time rather quickly, which may grow to a level that renders the navigation meaningless. Second, without human input or external references, the smartphone can hardly infer its initial position/velocity, which is the basis for distance calculation, since all that a smartphone can learn is its acceleration. This raises a practical concern, as users often need to start indoor navigation precisely when they are uncertain of their current whereabouts. In this paper, we present Bumping , a Bump-Aided Inertial Navigation method that significantly alleviates the above two problems. At the core of this method is a Bump Matching algorithm, which exploits the position information of the readily available speed bumps to provide useful references for the INS. The proposed method is easy to implement, requires no infrastructures, and incurs nearly zero extra energy. We conducted real experiments in tree parking garages of different environmental characteristics. The Bumping method produces an average position error of 4-5 m in these scenarios, improving the accuracy by up to 87.1 percent, compared to the basic inertial navigation method.