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引用次数: 3

摘要

提出了一种用于自主水下航行器水下电缆跟踪的传感器融合技术。本文的重点是解决基于光学视觉系统在水下环境中遇到的两个实际问题:(1)在图像中看不到电缆的情况下AUV的导航;(2)当图像中出现许多相似特征时,选择正确的电缆。提出的传感器融合方案利用航位推算位置的不确定性和电缆的二维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,避免了跟踪光学图像中出现的其他类似特征。该方法在图像预测区域内电缆特征不可见的情况下,利用电缆的先验映射进行水下航行器导航。利用“Twin-Burger 2”水下机器人进行了实验,验证了该算法的性能。实验结果表明,该方法能较好地解决上述实际问题。
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Underwater robots for cable following
A sensor fusion technique is proposed for autonomous underwater vehicles (AUVs) to track underwater cables. The focus of this paper is to solve the two practical problems encountered in optical vision based systems in underwater environments: (1) navigation of AUV when cable is invisible in the image; and (2) selection of the correct cable when there are many similar features appearing in the image. The proposed sensor fusion scheme uses the dead reckoning position uncertainty with a 2D position model of the cable to predict the region of interest in the image. This reduces the processing data, increases the processing speed and avoids tracking other similar features appearing in the optical image. The proposed method uses a priori map of the cable for AUV navigation when the cable features are invisible in the predicted region in the image. An experiment was conducted to test the performance of the proposed algorithm using the AUV "Twin-Burger 2". The experimental results obtained show how the proposed method handles the above-mentioned practical problems.
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