扩展卡尔曼滤波中惯性测量单元与里程计融合的航位推算导航性能比较

Kevin Carey, Benjamin Abruzzo, D. Harvie, C. Korpela
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引用次数: 0

摘要

本文旨在通过提供四种不同惯性测量单元(imu)之间的比较来帮助机器人和自动驾驶车辆的设计者,这些单元可用于在gps拒绝或仅惯性的情况下帮助车辆导航。设计了一种差动驱动地面车辆来携带多个同轴安装的不同imu,以便在平面环境中直接比较性能。实验重点研究了里程计传感器和imu对地面飞行器位姿误差的影响。提出了一种扩展的卡尔曼滤波方法,将里程测量和惯性测量融合在一起进行比较。评估的四个特定imu为:CNS 5000, Xsens 300, Microstrain GX5-35和Phidgets 1044,实验的基础真相由Optitrack运动捕捉系统(MCS)提供。最后,提出并讨论了选择imu的指标,合并了成本和性能考虑因素。虽然CNS 5000具有最佳的客观误差规格,但基于这些指标,Xsens 300展示了最佳的绝对性能,而Phidgets 1044提供了最佳的性价比。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Performance Comparison of Inertial Measurement Units Fused With Odometry in Extended Kalman Filter for Dead-Reckoning Navigation
This paper aims to aid robot and autonomous vehicle designers by providing a comparison between four different inertial measurement units (IMUs) which could be used to aid in vehicle navigation in a GPS-denied or inertial-only scenario. A differential-drive ground vehicle was designed to carry the multiple different IMUs, mounted coaxially, to enable direct comparison of performance in a planar environment. The experiments focused on the growth of pose error of the ground vehicle originating from the odometry senors and the IMUs. An extended Kalman Filter was developed to fuse the odometry and inertial measurements for this comparison. The four specific IMUs evaluated were: CNS 5000, Xsens 300, Microstrain GX5-35, and Phidgets 1044 and the ground truth for experiments was provided by an Optitrack motion capture system (MCS). Finally, metrics for choosing IMUs, merging cost and performance considerations, are proposed and discussed. While the CNS 5000 has the best objective error specifications, based on these metrics the Xsens 300 exhibits the best absolute performance while the Phidgets 1044 provides the best performance-per-dollar.
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