在室内环境中使用UWB定位的集成过方法的比较分析.
Rahul Ranjan1, Donggyu Shin2, Yoonsik Jung2
1Department of Computer and Electronic Convergence, Intelligent Robot Research Institute, Sun Moon University, Asan 31460, Republic of Korea.
Sensors (Basel, Switzerland)
|February 24, 2024
概括
这项研究通过整合过器来增强超宽带 (UWB) 定位. 带有低通波器 (EKF + LPF) 的扩展卡尔曼波器显著提高了室内定位准确度,并减少了噪音.
科学领域:
- 机器人和自动化 机器人和自动化
- 信号处理 信号处理
- 局部化系统 局部化系统
背景情况:
- 超宽带 (UWB) 系统提供高精度定位能力.
- 现有的过方法如移动平均 (MVG),卡尔曼过器 (KF) 和扩展卡尔曼过器 (EKF) 在降低噪音和准确性方面存在局限性.
- 提高UWB本地化对于机器人,自主导航和室内定位的应用至关重要.
研究的目的:
- 通过整合过技术来推进UWB本地化系统.
- 研究新的方法来提高UWB过的精度和降低噪声.
- 为了评估组合过方法的性能,特别是用低通过器 (EKF + LPF) 的扩展卡尔曼过器,与传统过器相比.
主要方法:
- 实现移动平均线 (MVG),卡尔曼波器 (KF),扩展卡尔曼波器 (EKF),以及与低通波器 (EKF + LPF) 结合的扩展卡尔曼波器.
- 在TurtleBot机器人平台上测试UWB系统,跨越多种轨迹路径 (方形,圆形,自由).
- 使用根平均平方误差 (RMSE) 和平均绝对误差 (MAE) 进行定位精度的定量分析.
主要成果:
- EKF+LPF表现出卓越的准确性,在正方形路径轨迹中实现了最低的RMSE值 (40.22 mm在X轴上,78.71 mm在Y轴上).
- 综合LPF方法的表现始终优于MVG,KF和EKF.
- 观察到平均绝对误差 (MAE) 的显著减少:正方形为3.39%,圆形为4.21%,自由路径为6.16%.
结论:
- 扩展卡尔曼波器和低通波器 (EKF + LPF) 的组合在提高UWB定位精度方面非常有效.
- 集成过方法为减少噪音和提高UWB系统的精度提供了强大的解决方案.
- 这项研究提供了一种经过验证的方法,可以使用UWB技术实现可靠的室内定位.
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