KTH-Royal Institute of Technology, SCI School, 100 44 Stockholm, Sweden.
KTH-Royal Institute of Technology, EECS School, 100 44 Stockholm, Sweden.
Sensors (Basel). 2022 Jul 5;22(13):5064. doi: 10.3390/s22135064.
This paper outlines challenges and opportunities in operating underwater robots (so-called AUVs) on a seaweed farm. The need is driven by an emerging aquaculture industry on the Swedish west coast where large-scale seaweed farms are being developed. In this paper, the operational challenges are described and key technologies in using autonomous systems as a core part of the operation are developed and demonstrated. The paper presents a system and methods for operating an AUV in the seaweed farm, including initial localization of the farm based on a prior estimate and dead-reckoning navigation, and the subsequent scanning of the entire farm. Critical data from sidescan sonars for algorithm development are collected from real environments at a test site in the ocean, and the results are demonstrated in a simulated seaweed farm setup.
本文概述了在海藻养殖场操作水下机器人（即 AUV）所面临的挑战和机遇。这一需求源于瑞典西海岸新兴的水产养殖业，那里正在开发大规模的海藻养殖场。在本文中，描述了操作挑战，并开发和演示了在操作中使用自主系统作为核心部分的关键技术。本文提出了一种在海藻养殖场中操作 AUV 的系统和方法，包括基于先前估计和推算导航的农场初始定位，以及随后对整个农场的扫描。从海洋测试场的真实环境中收集了用于算法开发的侧扫声纳关键数据，并在模拟的海藻养殖场设置中展示了结果。
