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Multisensor data fusion approach for terrain aided navigation of autonomous underwater vehicles

机译:多传感器数据融合方法用于自动水下航行器的地形辅助导航

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Autonomous navigation of underwater vehicles is a 'holy grail' of underwater robotics in many ways. For an AUV to continually estimate its pose (position and orientation) and operate within an unknown environment solely based on its onboard sensors is a very challenging problem. In this paper, commonly used AUV sensors such as Inertial Navigation System (INS), Forward Looking Sonar (FLS) and monocular CCD camera are considered. Paper also discusses a robust feature tracking technique from image sequences and thereby estimating the ego-motion. It also discusses about the trajectory recovery from the FLS and fusion of INS and FLS. Experimental results, conducted using the test-bed AUV 'NTU-UAV', are presented to highlight the performance of the proposed navigation scheme.
机译:在许多方面,水下航行器的自主导航是水下机器人技术的“圣杯”。对于AUV而言,仅凭其机载传感器连续估算其姿态(位置和方向)并在未知环境中运行是一个非常具有挑战性的问题。在本文中,考虑了惯性导航系统(INS),前视声纳(FLS)和单眼CCD摄像机等常用的AUV传感器。论文还讨论了一种基于图像序列的鲁棒特征跟踪技术,从而估计了自我运动。它还讨论了从FLS恢复轨迹以及INS和FLS融合的问题。提出了使用试验台AUV“ NTU-UAV”进行的实验结果,以突出提出的导航方案的性能。

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