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Adaptive Identification on the Group of Rigid-Body Rotations and its Application to Underwater Vehicle Navigation

机译:刚体旋转群的自适应辨识及其在水下航行器中的应用

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摘要

This paper reports a novel stable adaptive identifier on the group of rigid-body rotations, and its application to a sensor-calibration problem arising in underwater vehicle navigation. The problem addressed is the identification of an unknown rigid-body rotation map from input-output data. General least-squares (LS) and adaptive identification techniques are commonly employed to identify general linear maps from input-output data, but do not guarantee that the resulting identified map is a rigid-body rotation. At present, an LS singular value decomposition approach is the standard method for identification constrained to the group of rigid-body rotations. This paper reports the first exact adaptive identifier on the group of rigid-body rotations, together with a proof of asymptotic stability. Techniques for navigating underwater vehicles are reviewed, and the Doppler-alignment calibration problem is posed. The reported adaptive identifier is employed to solve this problem, and performance of this adaptive identifier is evaluated on both laboratory and field experimental data. The results reported herein compare favorably with results obtained via previously reported LS techniques. The methodology reported herein may be of broader interest because of its applicability to more general problems in the identification, dynamics, and control on the group of rigid-body motions
机译:本文报道了一种刚体旋转群上的新型稳定自适应标识符,并将其应用于水下车辆导航中出现的传感器校准问题。解决的问题是根据输入输出数据识别未知的刚体旋转图。通常使用通用最小二乘(LS)和自适应识别技术从输入-输出数据中识别通用线性图,但不能保证所得的识别图是刚体旋转。目前,LS奇异值分解方法是用于约束刚体旋转组的标准识别方法。本文报告了刚体旋转组上的第一个精确自适应标识符,以及渐近稳定性的证明。审查了水下航行器的导航技术,并提出了多普勒对准校准问题。使用报告的自适应标识符来解决此问题,并在实验室和现场实验数据上评估该自适应标识符的性能。本文报道的结果与通过先前报道的LS技术获得的结果相比具有优势。本文报道的方法论可能会引起广泛的关注,因为它适用于刚体运动组的识别,动力学和控制中的更一般的问题

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