基于视觉的足对足相对位置测量增强的行人惯性导航系统

Chi-Shih Jao, Yusheng Wang, A. Shkel
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引用次数: 21

摘要

在本文中,我们研究了如何通过使用脚到脚的视觉观察来增强自包含行人导航。主要贡献是一个测量模型,该模型使用零速度更新(ZUPT)和从鞋上的特征模式和相机获得的两只鞋之间的相对位置测量。该测量模型直接提供了行人三种位置状态和三种速度状态的补偿测量。检测所涉及的特征与周围环境无关,因此,所提出的系统在任何环境下都具有恒定的计算复杂度。将该系统的性能与独立ZUPT方法和相对距离辅助ZUPT方法进行了比较。仿真结果表明,该方法可将累计导航误差提高90%以上。实际实验结果表明,累计误差最大可改善85%,验证了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Pedestrian Inertial Navigation System Augmented by Vision-Based Foot-to-foot Relative Position Measurements
In this paper, we investigate how self-contained pedestrian navigation can be augmented by the use of foot-to-foot visual observations. The main contribution is a measurement model that uses Zero velocity UpdaTe (ZUPT) and relative position measurements between the two shoes obtained from shoe-mounted feature patterns and cameras. This measurement model provides directly the compensation measurements for the three position states and three velocity states of a pedestrian. The involved features for detection are independent of surrounding environments, thus, the proposed system has a constant computational complexity in any context. The performance of the proposed system was compared to a standalone ZUPT method and a relative-distance-aided ZUPT method. Simulation results showed an improvement in accumulated navigation errors by over 90%. Real-world experiments were conducted, exhibiting a maximum improvement of 85% in accumulated errors, verifying validity of the approach.
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