利用多波束声纳和深度传感器的协作式水下定位系统
Collaborative Aquatic Positioning System Utilising Multi-beam Sonar and Depth Sensors
AI总结：
本文提出一种通过全向水面航行器与水下ROV协作的定位系统，利用多波束声纳和深度传感器，在无固定基础设施下实现受限水下环境的精确导航。
摘要：
在受限环境中，水下机器人的精确定位对于检查和测绘任务至关重要，也是自主操作的前提。目前，尚无适用于受限水下环境实际应用的定位系统，这些系统不受环境光照和水体浊度限制，且具有足够的精度以实现可靠和可重复的导航。这一缺失对提升遥控潜水器（ROV）在此类场景中的能力构成了重大障碍。本文介绍了一种创新的定位系统，用于在受限、杂乱的水下环境中运行的ROV，该系统通过全向水面航行器与水下ROV的协作实现。提出并评估了一种基于可用传感器的数学公式。来自高保真仿真环境和工业储罐模型的高保真实验结果为该系统的原理验证提供了证据，并展示了其在真实场景中的实际可部署性。与许多先前方法不同，该系统不依赖固定基础设施或环境特征的跟踪，并且无需额外设备即可覆盖大型封闭区域。
英文摘要：
Accurate positioning of underwater robots in confined environments is crucial for inspection and mapping tasks and is also a prerequisite for autonomous operations. Presently, there are no positioning systems available that are suited for real-world use in confined underwater environments, unconstrained by environmental lighting and water turbidity levels, and have sufficient accuracy for reliable and repeatable navigation. This shortage presents a significant barrier to enhancing the capabilities of remotely operated vehicles (ROVs) in such scenarios. This paper introduces an innovative positioning system for ROVs operating in confined, cluttered underwater settings, achieved through the collaboration of an omnidirectional surface vehicle and an underwater ROV. A mathematical formulation based on the available sensors is proposed and evaluated. Experimental results from both a high-fidelity simulation environment and a mock-up of an industrial tank provide a proof of principle for the system and demonstrate its practical deployability in real-world scenarios. Unlike many previous approaches, the system does not rely on fixed infrastructure or tracking of features in the environment and can cover large enclosed areas without additional equipment.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
