面向回坞的AUV导航和路径规划研究

发布时间：2018-04-20 03:04

本文选题：自主水下航行器 + 回坞　；参考：《浙江大学》2016年硕士论文

【摘要】：近年来,自主水下航行器(Autonomous Underwater Vehicle,简称AUV)在海洋工程领域发挥了越来越重要的作用。一方面,日益复杂的应用场景对AUV续航能力和自主性的要求不断提高；另一方面,由于受自身携带能源和水下通信速率的限制,目前的大多数AUV水下工作的时间仍然较短,仍然需要频繁地布放和回收。水下回坞能够让AUV补充能源、上传数据并接受新的任务,正是解决这一矛盾的有效方案。本文基于实验室研制的小型AUV平台,开展了回坞过程的导航技术、路径规划、导航系统实现等工作,主要研究工作有：根据AUV回坞运动过程建立了三维导航模型,提出了改进的容积卡尔曼滤波(Modified Cubature Kalman Filter,简称MCKF)算法,大幅减少了滤波的计算量。针对超短基线(Ultra Short Baseline,简称USBL)辅助AUV回坞导航场景下存在的测量值延迟问题,分析对比了多种的延迟测量值滤波算法。同时,为避免测量野值(Outlier)对导航精度的影响,将MCKF和基于残差的野值检测方法和相结合,提出了抗野值MCKF滤波算法,进一步提高了滤波性能和稳定性。针对欠驱动AUV的运动特性,研究了基于Dubins路径的回坞路径规划算法。考虑到水底地形复杂,可能存在一些危险区域,提出了一种已知地形信息情况下基于图论的二维回坞路径规划算法,能够在多项式时间复杂度内得出最优Dubins路径。在此基础上,给出了一种适用于三维回坞场景的次优方案。在算法研究的基础上,基于小型AUV平台和MOOS (Mission Oriented Operating Suite,简称MOOS)开源软件,实现了整套回坞通信和导航系统。针对MOOS框架通信机制存在的不足,提出了基于Push模型的改进方案。并在MOOS框架下,实现了基于MCKF算法的导航程序,通过仿真和水池试验初步验证了其在实际应用中的可行性。
[Abstract]:In recent years, autonomous Underwater vehicle (AUV) plays an increasingly important role in the field of marine engineering. On the one hand, the increasingly complex application scenarios require the ability and autonomy of AUV to continue, on the other hand, due to the limitation of its own energy and underwater communication rate, most of the current AUV work under water is still relatively short time. There is still a need for frequent placement and recycling. Underwater redocking allows AUV to replenish energy, upload data and accept new tasks, which is an effective solution to this contradiction. Based on the small-scale AUV platform developed by the laboratory, the navigation technology, path planning and navigation system realization of the redocking process are carried out in this paper. The main research work is as follows: according to the AUV redocking process, a three-dimensional navigation model is established. An improved volumetric Cubature Kalman filter (MCKF) algorithm is proposed, which greatly reduces the computational complexity of the filter. Aiming at the problem of measurement delay in ultrashort base-line Ultra Short baseline (USBL-assisted AUV redocking) navigation scene, this paper analyzes and compares various filtering algorithms for delay measurement values. At the same time, in order to avoid the influence of outliers on navigation accuracy, an anti-outliers MCKF filtering algorithm is proposed by combining MCKF with outliers based on residuals, which further improves the filtering performance and stability. According to the motion characteristics of underactuated AUV, the redocking path planning algorithm based on Dubins path is studied. Considering the complexity of underwater terrain and the possibility of some dangerous regions, a graph theory-based two-dimensional redocking path planning algorithm based on graph theory is proposed, which can obtain the optimal Dubins path in polynomial time complexity. On this basis, a suboptimal scheme for 3D redocking scene is presented. On the basis of the algorithm research, the whole redocking communication and navigation system is realized based on the small AUV platform and the open source software of MOOS Mission Oriented Operating Suite. Aiming at the deficiency of MOOS framework communication mechanism, an improved scheme based on Push model is proposed. The navigation program based on MCKF algorithm is implemented under the framework of MOOS, and its feasibility in practical application is preliminarily verified by simulation and pool test.
【学位授予单位】：浙江大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：TN96

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