The ability to land on the seafloor expands the envelope of tasks that underwater vehicles can carry out during survey and inspection. However, even though remotely operated vehicles routinely land during their operations, autonomous underwater vehicles (AUVs) lack the sensing and data processing capabilities needed to identify safe, stable landing sites. Here, an algorithm is developed that uses millimeter-resolution (mm-resolution) bathymetry to detect regions where an AUV of known geometry can safely and stably land on the seafloor. The algorithm uses physical models that consider vehicle geometry, seafloor slope, roughness, friction, and currents. It can identify the most suitable of multiple candidate sites based on a landing cost function. The performance of the algorithm is evaluated using seafloor bathymetry data that was obtained using an AUV equipped with a high-resolution laser mapping system on the slopes of the Takuyo Daigo seamount in the Northwest Pacific. The algorithm successfully identified multiple landing sites along a 500-m transect on the slopes of the surveyed seamount. The study demonstrates that safe, reliable AUV landing operation is feasible in actual seafloor environments.

中文翻译：

---

使用高分辨率水深测量法实现水下航行器自主着陆

在海底着陆的能力扩大了水下航行器在调查和检查期间可以执行的任务范围。然而，即使远程操作的车辆在其操作过程中经常着陆，自主水下航行器 (AUV) 仍缺乏识别安全、稳定着陆点所需的传感和数据处理能力。在这里，开发了一种算法，该算法使用毫米分辨率（mm-resolution）水深测量来检测已知几何形状的 AUV 可以安全稳定地降落在海底的区域。该算法使用的物理模型考虑了车辆几何形状、海底坡度、粗糙度、摩擦力和水流。它可以根据着陆成本函数识别出多个候选站点中最合适的一个。该算法的性能使用海底测深数据进行评估，该数据使用配备高分辨率激光测绘系统的 AUV 在西北太平洋 Takuy​​o Daigo 海山的斜坡上获得。该算法在所调查的海山斜坡上沿着 500 米的横断面成功识别了多个着陆点。该研究表明，在实际海底环境中，安全、可靠的 AUV 着陆操作是可行的。