STTR Phase I: Low-Cost Autonomous Sailboats for Long-Term Ocean Missions

STTR 第一阶段：用于长期海洋任务的低成本自主帆船

• 批准号: 2213250
• 负责人: Jason Cortell
• 金额: $ 24.84万
• 依托单位: DYNAMIC LOCOMOTION, INC.
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-08-15 至 2024-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2213250&HistoricalAwards=false
• 关键词: STTR; Phase; Low; Cost; Autonomous

The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase I project is the development of new technologies to facilitate ocean data collection. Understanding the oceans is important for climate research, naval operations, maritime domain awareness, and ecosystem preservation, yet traditional data collection methods using research ships, commercial vessels, and buoys are cumbersome, expensive, and limited in their scope of discovery. While satellites have enabled remote data collection, they are affected by weather and limited in the types of data they collect. Uncrewed Surface Vessels (USVs) - robotic boats - are promising, but even today’s smallest oceangoing USVs are too costly for many applications. Thus, many regions of Earth’s oceans are rarely studied. The technology developed here aims to meet this need by enabling low-cost deployment of sensor-equipped robotic fleets. Better access to ocean data may improve understanding of the ocean and its resources, leading to better climate modeling, improved safety, economic gains, and more effective regulations. Further, ocean monitoring and surveillance is key to understanding ocean water quality, identifying contaminants, and devising strategies to prevent future contamination and pollution of the ocean’s waters. Ultimately, cost-effective oceanic data collection may help sustain and grow the ocean economy.This Small Business Technology Transfer (STTR) Phase I project aims to develop a small, low-cost, autonomous robotic sailboat that uses an innovative sail arrangement and weather-optimized navigation system. With a combination of affordability and utility, the technology represents a new approach for widespread oceanic data collection. This technology can be deployed virtually anywhere in the ocean, can be small (2 meters or less), and is 100% wind- and solar-powered. The research in this project seeks to further this technology by advancing two innovations: passive directional stability and weather-optimized navigation. Unlike most other robotic sailboats, the proposed USV does not need active steering to hold a course, once set. Further, the proposed USV has a navigation system that exploits the spatial and temporal variance in the weather and uses local weather data to direct the boats to navigate more efficiently. This STTR proposal seeks to address areas of high technical risk including stability of the steering system under various wind and water conditions, resistance to traveling excessively downwind during storms, effectiveness of the optimized navigation system in both actual and simulated weather conditions at locations worldwide, construction and performance of prototypes in lakes and oceans, and long-term resistance to marine environments.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

这项小型企业技术转让（STTR）第一阶段项目的更广泛影响/商业潜力是开发新技术以促进海洋数据收集。了解海洋对于气候研究、海军行动、海洋领域意识和生态系统保护非常重要，然而，使用研究船、商业船只和浮标的传统数据收集方法既繁琐又昂贵，而且发现范围有限。虽然卫星使远程数据收集成为可能，但它们受到天气的影响，收集的数据类型有限。无人水面船（usv）——机器人船——很有前途，但即使是今天最小的远洋无人水面船，对于许多应用来说也太昂贵了。因此，地球海洋的许多区域很少被研究。这里开发的技术旨在通过低成本部署配备传感器的机器人车队来满足这一需求。更好地获取海洋数据可以增进对海洋及其资源的了解，从而改进气候模型，提高安全性，提高经济效益，并制定更有效的法规。此外，海洋监测和监测是了解海洋水质、识别污染物和制定防止未来污染和污染海洋水域的策略的关键。最终，具有成本效益的海洋数据收集可能有助于维持和发展海洋经济。这项小型企业技术转移（STTR）第一阶段项目旨在开发一种小型、低成本、自主的机器人帆船，该帆船采用创新的帆布置和天气优化导航系统。该技术兼具可负担性和实用性，代表了一种广泛收集海洋数据的新方法。这项技术几乎可以部署在海洋的任何地方，可以很小（2米或更小），并且100%由风能和太阳能供电。该项目的研究旨在通过推进两项创新来进一步发展这项技术：被动定向稳定性和天气优化导航。与大多数其他机器人帆船不同，USV一旦设定航向，就不需要主动转向来保持航向。此外，拟议的USV有一个导航系统，利用天气的空间和时间变化，并使用当地的天气数据来指导船只更有效地导航。该STTR提案旨在解决高技术风险领域，包括在各种风和水条件下转向系统的稳定性，风暴期间过度顺风行驶的阻力，优化导航系统在全球各地实际和模拟天气条件下的有效性，湖泊和海洋原型的建造和性能，以及对海洋环境的长期抵抗。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。