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3D Autonomous Underwater Navigation Using Seabed Acoustic Sensing

机译:使用海底声波感应的3D自主水下导航

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Autonomous Underwater Vehicle (AUV) being a powerful tool for exploring and investigating ocean resources can be used in a large variety of oceanographic, industry and defense applications. Underwater navigation for AUV is still a challenging task and is one of the fundamental elements in modern robotics because the ability of AUV to correctly understand its position and attitude within the underwater environment is determinant for the success in the different applications. AUV navigation usually is based only on information obtained from Doppler Velocity Loggers, Inertial Navigation Systems, etc. due to the absence of an external reference sources. But this type of navigation is subjected to a continuously growing error due to the absence of the absolute position measurement (for example, received from GPS or GLONASS) which is typical for the majority of UAV applications. These measurements might be provided by observation of so-called feature points like in Unmanned Aerial Vehicles (UAV) case, but the big difference between acoustical and optical images makes it a rather difficult problem which solution needs detailed preliminary mapping of the operational seabed area. The new generation of acoustic imaging gives rise to the new approaches to AUV navigation based on the absolute velocity measurements. By analogy with the optical flow approach coming from the area of UAV the evolution of the seabed map produces the information related to the absolute motion of the AUV. The principal advantage of the proposed algorithm is that the fusion of the acoustic mapping and the Inertial Navigation System (INS) gives the absolute velocity of the vehicle with respect to the seabed. In some sense the suggested algorithm operates as multibeam Doppler Velocity Log (DVL), though in different way and in different environment. Even in the theory the DVL operates perfectly over the flat surface, but the suggested algorithm needs the presence of the relief and uses the evolution of the relief range obtained by sonar and measured from the ship to the seabed as a source of own speed.
机译:自主水下航行器(AUV)是一种用于探索和调查海洋资源的强大工具,可用于各种海洋学,工业和国防应用中。 AUV的水下导航仍然是一项艰巨的任务,并且是现代机器人技术的基本要素之一,因为AUV能够正确了解其在水下环境中的位置和姿态的能力决定了其在各种应用中的成功。由于缺少外部参考源,AUV导航通常仅基于从多普勒速度测井仪,惯性导航系统等获得的信息。但是,由于缺乏大多数无人机应用所典型的绝对位置测量值(例如,从GPS或GLONASS接收到的),因此这种类型的导航会遭受不断增长的误差。这些测量可能是通过观察所谓的特征点来提供的,例如在无人飞行器(UAV)情况下,但是声学和光学图像之间的巨大差异使其成为一个相当困难的问题,该解决方案需要对操作海床区域进行详细的初步制图。新一代的声学成像技术带来了基于绝对速度测量的AUV导航新方法。与来自无人机区域的光流方法类似,海床图的演变产生与AUV绝对运动有关的信息。所提出算法的主要优点是,声学映射和惯性导航系统(INS)的融合给出了车辆相对于海床的绝对速度。从某种意义上讲,尽管以不同的方式和环境,建议的算法仍可作为多光束多普勒速度测井(DVL)进行操作。即使在理论上,DVL可以在平坦表面上完美运行,但是建议的算法需要存在浮雕,并使用声纳获得的,从船到海底测量的浮雕范围的变化作为自身速度的来源。

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