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Fast Fingerprint Database Maintenance for Indoor Positioning Based on UGV SLAM

机译:基于UGV SLAM的室内定位快速指纹数据库维护

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摘要

Indoor positioning technology has become more and more important in the last two decades. Utilizing Received Signal Strength Indicator (RSSI) fingerprints of Signals of OPportunity (SOP) is a promising alternative navigation solution. However, as the RSSIs vary during operation due to their physical nature and are easily affected by the environmental change, one challenge of the indoor fingerprinting method is maintaining the RSSI fingerprint database in a timely and effective manner. In this paper, a solution for rapidly updating the fingerprint database is presented, based on a self-developed Unmanned Ground Vehicles (UGV) platform NAVIS. Several SOP sensors were installed on NAVIS for collecting indoor fingerprint information, including a digital compass collecting magnetic field intensity, a light sensor collecting light intensity, and a smartphone which collects the access point number and RSSIs of the pre-installed WiFi network. The NAVIS platform generates a map of the indoor environment and collects the SOPs during processing of the mapping, and then the SOP fingerprint database is interpolated and updated in real time. Field tests were carried out to evaluate the effectiveness and efficiency of the proposed method. The results showed that the fingerprint databases can be quickly created and updated with a higher sampling frequency (5Hz) and denser reference points compared with traditional methods, and the indoor map can be generated without prior information. Moreover, environmental changes could also be detected quickly for fingerprint indoor positioning.
机译:在过去的二十年中,室内定位技术变得越来越重要。利用机会信号(SOP)的接收信号强度指示器(RSSI)指纹是一种很有前途的替代导航解决方案。然而,由于RSSI由于其物理性质而在操作期间变化并且容易受到环境变化的影响,所以室内指纹识别方法的挑战之一是及时有效地维护RSSI指纹数据库。本文提出了一种基于自主开发的无人机平台NAVIS的快速更新指纹数据库的解决方案。在NAVIS上安装了多个SOP传感器,用于收集室内指纹信息,包括收集磁场强度的数字罗盘,收集光强度的光传感器以及收集预安装WiFi网络的接入点号和RSSI的智能手机。 NAVIS平台生成室内环境地图,并在地图处理过程中收集SOP,然后对SOP指纹数据库进行实时插值和更新。进行了现场测试,以评估该方法的有效性和效率。结果表明,与传统方法相比,可以以更高的采样频率(5Hz)和更密集的参考点快速创建和更新指纹数据库,并且无需事先信息即可生成室内地图。此外,还可以快速检测到环境变化,以进行指纹室内定位。

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