Department of Electrical and Electronic Engineering, The University of Manchester, Manchester M13 9PL, UK.
Institute of Mechanics and Ocean Engineering, Hamburg University of Technology, 21073 Hamburg, Germany.
Sensors (Basel). 2020 Oct 30;20(21):6203. doi: 10.3390/s20216203.
The inspection of aquatic environments is a challenging activity, which is made more difficult if the environment is complex or confined, such as those that are found in nuclear storage facilities and accident sites, marinas and boatyards, liquid storage tanks, or flooded tunnels and sewers. Human inspections of these environments are often dangerous or infeasible, so remote inspection using unmanned underwater vehicles (UUVs) is used. Due to access restrictions and environmental limitations, such as low illumination levels, turbidity, and a lack of salient features, traditional localisation systems that have been developed for use in large bodies of water cannot be used. This means that UUV capabilities are severely restricted to manually controlled low-quality visual inspections, generating non-geospatially located data. The localisation of UUVs in these environments would enable the autonomous behaviour and the development of accurate maps. This article presents a review of the state-of-the-art in localisation technologies for these environments and identifies areas of future research to overcome the challenges posed.
水下环境检测是一项极具挑战性的工作,如果环境复杂或受限,如核设施和事故现场、码头和船坞、液体储罐、淹没的隧道和下水道等,检测工作会变得更加困难。由于这些环境通常存在危险或不适合人工检测,因此会使用无人水下机器人(UUV)进行远程检测。由于进入受限和环境限制,例如低光照水平、浑浊度和缺乏明显特征,因此无法使用为大型水体开发的传统定位系统。这意味着 UUV 的能力严重限于手动控制的低质量视觉检测,生成非地理空间定位的数据。在这些环境中对 UUV 进行定位可以实现自主行为并开发精确地图。本文综述了这些环境下的定位技术的最新进展,并确定了未来研究的领域,以克服所面临的挑战。