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Side-Scan Sonar Data-Driven Coverage Path Planning: A Comparison of Approaches*

机译：侧扫声明数据驱动的覆盖路径规划：方法 * 的比较

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Side-scan sonar mapping of an unknown large-scale seafloor area by a marine vehicle is nowadays very common. It is also important that a-priori unknown interesting parts of the seafloor area are scanned in more detail, i.e. sonified from both sides. However, completely autonomous and time-efficient coverage path (re)planning for such missions is still an open issue. In contrast to the standard overlap-all-sonar-ranges lawnmower pattern offline static coverage problem solution for side-scan sonar missions, in this paper two online sonar data-driven coverage algorithms are proposed as extensions of authors' prior work. Analytical upper and lower bounds on performance of the proposed coverage planning algorithms are given and validated through extensive mission parameters variation simulations. Statistical performance analysis of the proposed coverage planning algorithms' performance shows significant complete coverage time efficiency improvements w.r.t. the classical unadaptive lawnmower approach. Also, a detailed comparison of coverage planning algorithms proposed by the authors so far is provided.
机译：如今，船用车辆的未知大型海底区域的侧扫声纳映射是非常普遍的。同样重要的是，扫描海底区域的a-priori的未知有趣部分，即从两侧混淆。但是，对于此类任务的完全自主和节省的覆盖路径（RE）规划仍然是一个开放的问题。与标准重叠all-sonar-ranges割草机模式离线静态覆盖问题解决方案的侧扫扫描声纳任务解决方案，在本文中，两个在线声纳数据驱动的覆盖算法被提出为作者前后工作的扩展。通过广泛的任务参数变化模拟给出并验证了所提出的覆盖计划算法的分析上限和下限。拟议覆盖计划算法的统计性能分析显示出显着完全的覆盖时间效率改进W.R.T.经典的无拘无束割草机方法。此外，提供了到目前为止提出的作者提出的覆盖计划算法的详细比较。

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