人机共享环境下基于Wi-Fi指纹的室内定位方法

doi:10.13973/j.cnki.robot.180307

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赵林生, 王鸿鹏, 刘景泰. 人机共享环境下基于Wi-Fi指纹的室内定位方法[J]. 机器人, 2019, 41(3): 404-413.DOI: 10.13973/j.cnki.robot.180307. ZHAO Linsheng, WANG Hongpeng, LIU Jingtai. An Indoor Localization Method Based on Wi-Fi Fingerprint in the Human-Robot Shared Environment. ROBOT, 2019, 41(3): 404-413. DOI: 10.13973/j.cnki.robot.180307.

摘要针对服务机器人和行人的室内全局定位问题，提出一种人机共享环境下基于Wi-Fi指纹的室内定位方法.首先，采用核主成分分析法（KPCA）从双频段的Wi-Fi信号中提取一种设备无关的鲁棒位置指纹，用于Wi-Fi指纹定位.然后，为了提高行人定位的稳定性和精确度，结合行人航迹推算（PDR）的定位方法，设计了一种基于选择更新粒子滤波（SUPF）的Wi-Fi/PDR组合定位算法.在该算法中，利用PDR对移动场景下的Wi-Fi定位结果进行了初步校正，并通过定义自适应大小的可信空间对校正后的结果进行评估，从而在数据融合之前剔除不可信的Wi-Fi定位估计.最后，在实际场景下开展了定位实验，Wi-Fi/PDR组合定位的平均定位误差约为2 m，实验结果表明所提出的方法提升了定位系统的精确度和鲁棒性.

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	赵林生
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关键词 ：服务机器人, Wi-Fi指纹定位, 共融机器人, 行人航迹推算, 粒子滤波

Abstract：An indoor localization method is proposed based on Wi-Fi fingerprint in the human-robot shared environment, in order to solve the problem of indoor global localization for service robots and pedestrians. Firstly, the device-independent robust position fingerprint is extracted from dual-band Wi-Fi signals by kernel principal component analysis (KPCA) for WiFi fingerprinting. Then, combining with the pedestrian dead reckoning (PDR) method, a Wi-Fi/PDR integrated positioning algorithm is presented based on selective update particle filter (SUPF) to improve the stability and the accuracy of pedestrian positioning. In the algorithm, the Wi-Fi localization results in the moving scene are preliminarily corrected using PDR, and the corrected results are evaluated by defining the trusted space of an adaptive size, so that untrusted Wi-Fi localization estimations are removed before the data fusion. Finally, localization experiments are carried out in a real scenario, and the average positioning error of the Wi-Fi/PDR integrated positioning algorithm is about 2 m. Experimental results demonstrate that the proposed method improves the accuracy and the robustness of the positioning system.

Key words： service robot Wi-Fi fingerprint localization tri-co (coexisting-cooperative-cognitive) robot pedestrian dead reckoning (PDR) particle filter

收稿日期: 2018-04-25 录用日期: 2018-08-27

TP242.6

基金资助:国家自然科学基金（61375087，61573198）；天津市应用基础与前沿技术研究计划（15JCZDJC31200，14ZCD2GX00798）.

通讯作者: 刘景泰 E-mail: liujt@nankai.edu.cn

作者简介: 赵林生(1995-),男,硕士生.研究领域:服务机器人,室内定位,多模态环境感知.
王鸿鹏(1979-),男,博士,副教授.研究领域:机器人与智能系统,自然生态环境智能化监测.
刘景泰(1964-),男,博士,教授.研究领域:机器人技术,计算机应用与信息自动化系统,智能科学与技术.

链接本文:

https://robot.sia.cn/CN/10.13973/j.cnki.robot.180307 或 https://robot.sia.cn/CN/Y2019/V41/I3/404

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