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位置推定arXiv:1911.03754

Wi-Fiとオドメトリを組み合わせた低コスト・低複雑度の屋内位置推定

Hybrid Localization: A Low Cost, Low Complexity Approach Based on Wi-Fi and Odometry

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Wi-Fiによる位置推定とオドメトリを融合し、屋内で移動ロボットの位置誤差を低減するアルゴリズムを実環境計測に基づき提案・検証した論文。

著者: Letizia Moro, Hani Mehrpouyan

分類: cs.RO, eess.SP

原文アブストラクト

Localization in indoor environments is essential to further support automation in a wide array of scenarios. Moreover, direction-of-arrival knowledge is essential to supporting high speed millimeter-wave (mmWave) links in indoor environments, since most mmWave links are of a line-of-sight nature to combat the high pathloss in this band. Accurate wireless localization in indoor environments, however, has proved a challenging task due to multi-path fading. Additionally, due to the effects of multi-path fading, methods such as trilateration alone do not result in accurate localization. As such, in this paper we propose to combine the knowledge of wireless localization methods with that of odometry sensors to track the location of a mobile robot. This paper presents significant real-world localization measurement results for both Wi-Fi and odometry in diverse environments at the Boise State University campus. Using these results, we devise an algorithm to combine data from both odometry and wireless localization. This algorithm is shown in hardware testing to reduce the localization error for a mobile robot

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