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Autonomous navigation based on iSAM and GPS filter for AUV

机译:基于ISAM和GPS滤波器的AUV自主导航

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As we all known, autonomous navigation system is the basic of AUV movement, besides, accurate position estimation and reliable measurement are the keys of it. In order to avoid accumulating position errors in the long voyage by using navigation algorithm, we can depend on GPS. Due to the influence of diving and floating process, GPS data would slip. The slips affect the accuracy of navigation seriously and cause errors for AUV in path planning. Little slips can be accepted, while we can't tolerate large slips up to several hundred meters. This paper proposed the GPS filter algorithm, which combined with navigation algorithm such as DR, EKF and iSAM (incremental smoothing and mapping). In order to verify the validity and feasibility of the combination of navigation algorithm and the proposed algorithm, Sea trials were carried out on the high seas of the Yellow Sea. Experimental results and analysis show that the autonomous navigation approach combined GPS filter with navigation algorithm improves the accuracy of navigation compared with conventional method, at the same time iSAM has a higher accuracy than the other two algorithms.
机译:正如我们所知道的,自主导航系统是AUV运动的基本,此外,准确的位置估计和可靠的测量是它的键。为了避免通过使用导航算法在长途航行中累积位置误差,我们可以依赖于GPS。由于潜水和浮动过程的影响,GPS数据会滑倒。 Slips严重影响导航的准确性并导致路径规划中AUV的错误。可以接受小滑动,而我们不能容忍大量的大型滑块,高达几百米。本文提出了GPS滤波器算法,该算法与导航算法相结合,如DR,EKF和ISAM(增量平滑和映射)。为了验证导航算法和所提出的算法组合的有效性和可行性,在黄海的海域中进行海洋试验。实验结果和分析表明,与传统方法相比,具有导航算法的自主导航方法GPS滤波器提高了导航的准确性,同时ISAM具有比其他两种算法更高的精度。

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