MRI: Acquisition of a Heterogeneous Networked Instrument for Aquatic Exploration and Intelligent Sampling

MRI：获取用于水生勘探和智能采样的异构网络仪器

• 批准号: 1531322
• 负责人: Ryan Smith
• 金额: $ 39.21万
• 依托单位: Fort Lewis College
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-09-01 至 2016-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1531322&HistoricalAwards=false
• 关键词: MRI; Acquisition; Heterogeneous; Networked; Instrument

The goal of this project is to address water-related issues in the Four Corners Region through an automated, robotic monitoring system composed of multiple cooperating and communicating autonomous robots that serve as an integrated monitoring system. Aquatic observation and monitoring is key to understanding and ultimately predicting long-term effects of urbanization, water storage and climate change. Effective observation and monitoring requires simultaneous measurement of multiple water properties, which must be made rapidly to capture variations in both space and time. Autonomous aquatic vehicles provide a cost-effective, non-intrusive, and a repeatable way of observing aquatic ecosystems up close, and at an unprecedented resolution. With these modern robots having such amazing capabilities, the main challenge in this project is to determine where and when to deploy the robots to gain the most understanding of our water resources. Through this research effort, the research will not only learn more about water resources in the Four Corners Region, but it will additionally develop algorithms and intelligent sampling strategies that can be utilized for studying any aquatic environment around the world, e.g., oceans, lakes, rivers, etc. Aquatic wireless sensor networks are instrumental to a better scientific understanding of aquatic ecosystems, environmental monitoring, surveillance for defense applications, homeland security, and aquaculture, providing a wealth of applications to the community beyond those directly studied in this proposal.Effective observation and quantification of spatiotemporally dynamic processes occurring in aquatic environments, e.g., the ocean, requires simultaneous measurement of diverse water properties, which must be made rapidly to capture the both the spatial and temporal variability of multiple simultaneous interactions. This cannot be done by traditional oceanographic methods involving infrequent and sparse measurements from ships, buoys and drifters. The research must employ an adaptive-sampling, heterogeneous team of robotic assets that can perform in situ feature recognition and event response with accurate localization to plug a substantial gap in understanding of a range of processes: physical (e.g., tidal mixing and seasonal overturn), chemical (e.g., nutrient upwelling and hypoxia), and biological (e.g., harmful algal blooms). Successfully orchestrating a multi-vehicle, deployment additionally requires a robust, rapid and cost-effective communication network. Only when all these components, which form an aquatic robotic, sensing system, are in synchronous operation can scientists begin to improve our overall understanding of the complex aquatic environment. This project will acquire and implement a heterogeneous networked instrument composed of three complementary aquatic robots; two autonomous surface vehicles and one autonomous underwater vehicle. These networked robots will enhance a program of research in marine robotics, networking, and deliberative planning to address fundamental questions in marine biology, oceanography, and aquatic biogeochemistry by addressing critical water quality issues within the Four Corners Region. The proposed instrument acquisition will provide a cost-effective test bed for the validation of planning and sampling strategies for large-scale, heterogeneous robotic networks. Specifically, the proposed system will enable researchers to efficiently and cost-effectively develop, test and validate coordinated, multi-vehicle control algorithms and strategies for intelligent aquatic sampling.

该项目的目标是通过一个自动化的机器人监测系统来解决四角地区与水有关的问题，该系统由多个协作和通信的自主机器人组成，作为一个综合监测系统。水生观察和监测是了解和最终预测城市化、水储存和气候变化长期影响的关键。有效的观察和监测需要同时测量多种水的性质，必须迅速进行，以捕捉空间和时间上的变化。自主水上交通工具提供了一种具有成本效益、非侵入性和可重复的近距离观察水生生态系统的方法，并且具有前所未有的分辨率。由于这些现代机器人拥有如此惊人的能力，这个项目的主要挑战是确定何时何地部署机器人，以获得对水资源的最大了解。通过这项研究，不仅可以进一步了解四角地区的水资源，还可以开发算法和智能采样策略，用于研究世界上任何水生环境，如海洋、湖泊、河流等。水生无线传感器网络有助于更好地科学理解水生生态系统、环境监测、国防应用监测、国土安全和水产养殖，为社区提供了丰富的应用，超出了本提案直接研究的范围。有效地观测和量化发生在水环境（如海洋）中的时空动态过程，需要同时测量不同的水性质，这些性质必须快速进行，以捕捉多个同时相互作用的空间和时间变异性。传统的海洋学方法不可能做到这一点，这些方法涉及从船舶、浮标和漂流船进行的不频繁和稀疏的测量。这项研究必须采用一个适应性采样、异构的机器人资产团队，能够进行原位特征识别和事件响应，并精确定位，以填补对一系列过程理解的实质性空白：物理（例如潮汐混合和季节性翻转）、化学（例如营养物质上涌和缺氧）和生物（例如有害藻华）。成功地协调多车辆部署，还需要一个强大、快速和经济的通信网络。只有当构成一个水生机器人传感系统的所有这些组成部分同步运行时，科学家们才能开始提高我们对复杂水生环境的整体认识。本项目将获取并实现由三个互补的水生机器人组成的异构网络化仪器；两个自主水面航行器和一个自主水下航行器。这些网络机器人将通过解决四角地区的关键水质问题，加强海洋机器人、网络和审议规划方面的研究项目，以解决海洋生物学、海洋学和水生生物地球化学方面的基本问题。提出的仪器采集将为大规模异构机器人网络的规划和采样策略的验证提供一个具有成本效益的测试平台。具体来说，该系统将使研究人员能够高效、经济地开发、测试和验证用于智能水生采样的协调、多车辆控制算法和策略。