Collaborative Research: Improved Vehicle Autonomy in Geophysical Flows

合作研究：提高地球物理流中的车辆自主性

• 批准号: 1760369
• 负责人: Mongying Hsieh
• 金额: $ 28.17万
• 依托单位: University of Pennsylvania
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-07-01 至 2020-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1760369&HistoricalAwards=false
• 关键词: Collaborative; Research; Improved; Vehicle; Autonomy

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.

自主水下和水面航行器（auv和asv）网络允许对海洋进行直接和连续的监测。新的部署策略需要从相对较少的船只中获得最大的覆盖范围。这将需要更好地理解控制地球物理流动（如洋流）中运输的结构。新的研究结果表明，通过引入洋流动力学模型，改进了AUV/ASV运动规划和自适应采样策略。然而，这些潮流不断变化，显然是不可预测的，这使得充分利用它非常具有挑战性。该项目的目标是更好地了解洋流中主导结构的动力学，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使用寿命。为了实现项目目标，研究目标是：1)识别和评估与自动驾驶汽车导航和控制最相关的海洋表面流中控制运输的关键运动学特征；2)为自动驾驶汽车团队开发一个通用的数学和控制框架，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；3)利用WHOI Jetyaks将控制框架应用于盐楔锋面的跟踪，以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现有的研究基础设施。这项工作解决了理论和实验方面的挑战，需要开发一个通用的数学和控制框架，将地球物理流体动力学应用于自主车辆个人和网络团队的新规划、导航和控制策略的开发。