步行者定位与步行智能误差估计和补偿通过融合UWB和IMU数据的位置
Fabian Hölzke1, Hagen Borstell2, Frank Golatowski1
1Institute of Applied Microelectronics and CE, University of Rostock, 18059 Rostock, Germany.
Sensors (Basel, Switzerland)
|July 11, 2023
概括
本研究引入了一种使用超宽带 (UWB) 和惯性测量单元 (IMU) 数据实时室内定位误差估计的新方法. 它通过在操作过程中准确评估本地化准确度来提高移动机器应用程序的可靠性和安全性.
科学领域:
- 机器人和自动化 机器人和自动化
- 室内定位技术 室内定位技术
- 传感器融合式传感器
背景情况:
- 可靠的操作员定位对于工业环境中安全有效的自主移动机器操作至关重要.
- 现有的室内定位系统经常在准确性和可靠性方面扎,特别是在具有挑战性的环境中.
研究的目的:
- 开发和评估一种实时估计和减轻室内环境中定位错误的方法.
- 通过整合脚部安装的惯性测量单元 (IMU) 的数据来提高超宽带 (UWB) 定位系统的可靠性.
主要方法:
- 从UWB位置测量构建虚拟步进向量,并将其与IMU衍生的步进向量进行比较.
- 使用独立的UWB和IMU测量来估计UWB定位的实时可靠性.
- 采用两种矢量类型的松散合过,以减轻定位错误并提高准确性.
主要成果:
- 提出的方法成功地估计了每步的定位错误.
- 在不同环境中的评估表明,定位准确性有所提高,特别是在视线受阻和UWB基础设施稀疏的条件下.
- 该系统有效地缓解了对UWB定位的模拟伪造攻击.
结论:
- 运行时判断定位质量可以通过比较UWB和IMU重建的用户步伐来实现.
- 该方法是稳固的,不需要环境特定的参数调整,为检测各种定位错误状态提供了一个有希望的方法.
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