惯性测量装置
计算机科学
非视线传播
扩展卡尔曼滤波器
卡尔曼滤波器
巡逻
平滑的
实时计算
移动机器人
人工智能
计算机视觉
机器人
无线
电信
地理
考古
作者
Mahmoud Elsanhoury,J. Nieminen,Petri Välisuo,Akpojoto Siemuri,Janne Koljonen,Mohammed Elmusrati,Heidi Kuusniemi
标识
DOI:10.1109/ipin57070.2023.10332542
摘要
Indoor positioning systems (IPSs) are the foundations for all indoor location-based services and applications. In this article, we present a precise and robust IPS using ultra wide-band (UWB) technology fused with an inertial measurement unit (IMU). Both technologies are integrated to account for the non-line-of-sight (NLOS) problems arising in a dense challenging environment found within an industrial laboratory in Finland. Besides the conventional estimation techniques e.g. extended Kalman filter (EKF), we employ the Rauch-Tung-Striebel (RTS) smoothing algorithm in addition to a multivariate regression-based offset compensation method to improve the overall positioning accuracy of the system. The recommended number of distributed UWB anchors versus the coverage area is also discussed and tested in this article. The experiments were held by a patrolling mobile robot with millimeter accuracy, which acted as a ground truth reference to all used algorithms. The positioning estimation results showed a superior performance by the proposed method (UWB/IMU EKF-RTS-LR) with mean accuracy of 4.7 cm, and 9.6 cm for more than 95% of the time.
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