论文标题
覆盖道路计划，并通过自动水下车辆的轨道间距适应
Coverage Path Planning with Track Spacing Adaptation for Autonomous Underwater Vehicles
论文作者
论文摘要
在本文中，我们解决了矿山对策（MCM）搜索问题，即使用侧面的声纳来调查海床的自动驾驶汽车（AUV）。我们提出了一种覆盖路径计划方法，该方法适应了AUV轨道间距，目的是收集更好的数据。我们通过将覆盖范围重叠在传感器范围的尾部中的重叠来实现，从而预期数据质量最低。为了评估算法，我们从三个ATSEA实验中收集了数据。自适应调查使AUV可以从高估传感器范围并导致区域覆盖范围的情况下恢复。在另一个实验中，自适应调查显示，近30％的“最坏”数据的数据质量提高了4.2％。
In this paper we address the mine countermeasures (MCM) search problem for an autonomous underwater vehicle (AUV) surveying the seabed using a side-looking sonar. We propose a coverage path planning method that adapts the AUV track spacing with the objective of collecting better data. We achieve this by shifting the coverage overlap at the tail of the sensor range where the lowest data quality is expected. To assess the algorithm, we collected data from three at-sea experiments. The adaptive survey allowed the AUV to recover from a situation where the sensor range was overestimated and resulted in reducing area coverage gaps. In another experiment,the adaptive survey showed a 4.2% improvement in data quality for nearly 30% of the 'worst' data.
