CAREER: Autonomous Underwater Power Distribution System for Continuous Operation

职业：连续运行的自主水下配电系统

• 批准号: 1921060
• 负责人: Nina Mahmoudian
• 金额: $ 35.23万
• 依托单位: Purdue University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-01-01 至 2022-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1921060&HistoricalAwards=false
• 关键词: CAREER; Autonomous; Underwater; Power; Distribution

This CAREER project responds to an urgent need to develop mobile power distribution systems that lower deployment and operating costs while simultaneously increasing network efficiency and response in dynamic and often dangerous physical conditions. The significant need for an efficient and effective mobile power distribution system became evident during search and rescue/recovery missions following the Japan tsunami and the disappearance of the Malaysia MH370 airplane. The technology outcomes from this project will apply to a broad range of environments (in space, air, water or on ground) where the success of long-term robotic network missions is measured by the ability of the robots to operate, for an extended period of time, in highly dynamic and potentially hazardous environments. These advanced features will provide the following advantages: efficiency, efficacy, guaranteed persistence, enhanced performance, and increased success in search/rescue/recovery/discovery missions. Specifically, this project addresses the following technology problems as it translates from research discovery toward commercial application: inflated energy use currently required when the autonomous vehicles break from mission to return to recharging station; lack of multi-robot coordination needed to take into account both fundamental hardware and network science challenges necessary to respond to energy needs and dynamic environment conditions. By addressing these gaps in technology, this work establishes the theoretical, computational, and experimental foundation for mobile power delivery and onsite recharging capability. Moreover, the new technology developed in this project is universally adaptable for disparate autonomous vehicles especially autonomous underwater vehicles (AUVs). In more technical terms, this project creates network optimization and formation strategies that will enable a power distribution system to reconfigure itself depending on the number of operational autonomous vehicles and recharging specifications to meet overall mission specifications, the energy consumption needs of the network, situational conditions, and environmental variables. Such a system will play a vital role in real-time controlled applications across multiple disciplines such as sensor networks, robotics, and transportation systems where limited power resources and unknown environmental dynamics pose major constraints. In addition to addressing technology gaps, undergraduate and graduate students will be involved in this research and will receive interdisciplinary education/ innovation/ technology translation/ outreach experiences through: developing efficient network energy routing, path planning and coordination strategies; designing and creating experimental test-beds and educational platforms; and engaging K-12th grade students in Science, Technology, Engineering and Math including those from underrepresented groups. This project engages Michigan Tech's Great Lake Research Center (GLRC) and Center for Agile Interconnected Microgrids (AIM) to develop experimental test-beds and conduct tests that validate the resulting methods and algorithms, and ultimately, facilitate the technology translation effort from research discovery toward commercial reality.

该CARICE项目满足了开发移动配电系统的迫切需求，该系统可降低部署和运营成本，同时提高网络效率和在动态且往往危险的物理条件下的响应能力。在日本海啸和马来西亚MH370飞机失踪后的搜救/恢复任务中，对高效和有效的移动配电系统的重大需求变得明显。该项目的技术成果将适用于广泛的环境(空间、空气、水或地面)，在这些环境中，长期机器人网络任务的成功与否取决于机器人在高度动态和潜在危险的环境中长时间运行的能力。这些高级功能将提供以下优势：效率、有效性、有保证的持久性、增强的性能，以及在搜索/救援/恢复/发现任务中的更大成功。具体地说，该项目在从研究发现转化为商业应用的过程中解决了以下技术问题：自动车辆从任务中断返回充电站时目前所需的过度能源使用；缺乏考虑基本硬件和网络科学挑战以应对能源需求和动态环境条件所需的多机器人协调。通过解决这些技术差距，这项工作为移动电力输送和现场充电能力奠定了理论、计算和实验基础。此外，该项目开发的新技术对不同的自主机器人，特别是自主水下机器人(AUV)具有普遍的适应性。在更多的技术术语中，该项目创建了网络优化和编队策略，使配电系统能够根据运行的自动驾驶车辆的数量和充电规格进行自我重新配置，以满足总体任务规格、网络的能源消耗需求、情况条件和环境变量。这样的系统将在传感器网络、机器人和交通系统等多个学科的实时受控应用中发挥重要作用，在这些领域，有限的电力资源和未知的环境动态构成了主要限制。除了解决技术差距，本科生和研究生将参与这项研究，并将通过以下方式获得跨学科教育/创新/技术转化/推广经验：制定有效的网络能源路由、路径规划和协调战略；设计和创建实验试验台和教育平台；吸引K-12年级的学生学习科学、技术、工程和数学，包括来自代表性不足群体的学生。该项目与密歇根理工学院大湖研究中心(GLRC)和敏捷互联微电网中心(AIM)合作，开发实验试验台并进行测试，以验证所产生的方法和算法，最终促进技术从研究发现向商业现实的转化。