Collaborative Research: Improved Vehicle Autonomy in Geophysical Flows

自主水下和水面航行器（AUV和ASV）网络可以直接和连续地监测海洋。需要新的部署战略，以便从相对较少的船只中获得最大的覆盖范围。这将需要更好地了解控制洋流等地球物理流动的结构。新的结果表明，AUV/ASV的运动规划和自适应采样策略的改进，结合海流动力学模型。然而，这些电流不断变化，显然是不可预测的，这使得充分利用极具挑战性。该项目的目标是更好地了解洋流中主要结构的动力学，并探索它们对AUV/ASV自主性的影响。此外，这项工作将为单个车辆和车辆团队提供强大的运动控制策略，以跟踪所需的结构边界，同时利用环境动态来延长运行寿命。为了实现项目目标，研究目标是：1）识别和评估控制与自主车辆导航和控制最相关的海洋表面流中的运输的关键运动学特征，2）为自主车辆团队开发通用数学和控制框架，其利用海洋流中的关键运输控制特征来改进动态和不确定环境的导航和监测，和3）应用控制框架的跟踪盐楔前锋使用WHOI Jetyaks建立从实验室到海洋的过渡。这项工作有一个重要的实验组成部分，利用PI的现有研究基础设施。 这项工作解决了开发一个通用数学和控制框架所需的理论和实验挑战，该框架将地球物理流体动力学应用于为个人和网络化的自动驾驶车辆团队开发新的规划，导航和控制策略。

Networks of autonomous underwater and surface vehicles (AUVs and ASVs) allow direct and continuous monitoring of the ocean. New deployment strategies are needed to obtain maximum coverage from a relatively small number of vessels. This will require better understanding of the structures controlling transport in geophysical flows such as ocean currents. New results show that AUV/ASV motion planning and adaptive sampling strategies are improved by incorporating models of ocean current dynamics. However, these currents change continually and apparently unpredictably, and this makes it highly challenging to take full advantage. The goals of this project are to better understand the dynamics of the dominant structures in ocean currents, and to explore their impact on AUV/ASV autonomy. Additionally, this work will produce robust motion control strategies for both single vehicles and teams of vehicles, to track desired structure boundaries, while leveraging the environmental dynamics to prolong operational lifespan. In pursuit of the project goals, the research objectives are to: 1) identify and evaluate key kinematic features that control transport in oceanic surface flows of greatest relevance to autonomous vehicle navigation and control, 2) develop a general mathematical and control framework for teams of autonomous vehicles that leverages key transport controlling features in oceanic flows for improved navigation and monitoring of dynamic and uncertain environments, and 3) apply the control framework to the tracking of salt wedge fronts using the WHOI Jetyaks to establish the transition from the laboratory to the ocean. This work has a significant experimental component that leverages the PIs' existing research infrastructure. The work addresses the theoretical and experimental challenges needed to develop a general mathematical and control framework for applying geophysical fluid dynamics to the development of novel planning, navigation, and control strategies for individual and networked teams of autonomous vehicles.