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Autonomous target tracking by Twin-Burger 2

机译:双汉堡2的自主目标跟踪

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摘要

In this paper, a sensor fusion technique is proposed for autonomous underwater vehicles (AUV) to track underwater cables. The work presented here is an extension of the authors' previously proposed vision based cable tracking system (1997, 1998). The focus of this paper is to solve the two practical problems encountered in vision based systems; namely (1) navigation of AUV when cable is invisible in the image, and (2) selection of the correct cable (interested feature) when there are many similar features appearing in the image. The proposed sensor fusion scheme uses deadreckoning position uncertainty with a 2D position model of the cable to predict the region of interest in the image. This reduces the processing data increasing processing speed and avoids tracking other similar features appearing in the image. The proposed method uses a 2D position model of the cable for AUV navigation when the cable features are invisible in the predicted region. An experiment is conducted to test the performance of the proposed system using the AUV "Twin-Burger 2". The experimental results presented in this paper shows how the proposed method handles the above mentioned practical problems.
机译:本文提出了一种传感器融合技术,用于跟踪水下电缆的自主水下车辆(AUV)。这里提出的工作是作者以前提出了基于视觉的电缆跟踪系统的延伸(1997,1998)。本文的重点是解决基于视觉系统中遇到的两个实际问题;即auv的(1)AUV的导航当电缆在图像中是看不见的,并且(2)在图像中出现许多类似的功能时,选择正确的电缆(感兴趣的功能)。所提出的传感器融合方案使用偏移位置不确定性与电缆的2D位置模型来预测图像中的感兴趣区域。这减少了处理数据,提高了处理速度,并避免跟踪图像中出现的其他类似功能。当电缆特征在预测区域中不可见时,所提出的方法使用电缆的2D位置模型进行AUV导航。进行实验以使用AUV“双汉堡2”来测试所提出的系统的性能。本文提出的实验结果表明,该方法如何处理上述实际问题。

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