Underwater Robot Navigation and Localization During Recovery by Optical Homing and Penning

水下机器人在回收过程中通过光学寻的和潘宁进行导航和定位

• 批准号: 2330416
• 负责人: Md Jahidul Islam
• 金额: $ 59.95万
• 依托单位: University of Florida
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2024
• 资助国家: 美国
• 起止时间: 2024-01-01 至 2026-12-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2330416&HistoricalAwards=false
• 关键词: Underwater; Robot; Navigation; Localization; During

For autonomous underwater robots the ability to operate for long periods of time and then return back safely is a critical feature in a range of important applications, such as subsea inspection, remote surveillance, and seasonal monitoring. A major challenge for a robot in such long-term missions is to estimate its location accurately since GPS signals cannot penetrate the ocean’s surface, and Wi-Fi or radio communication infrastructures are not available underwater. Using a dedicated surface vessel for acoustic referencing or coming up to the water surface for GPS signals are power hungry, computationally expensive, and often impossible (in stealth applications). This project will make scientific and engineering advances by using a novel optics-based framework and on-board AI technologies to solve this problem. The algorithms and systems will allow underwater robots to estimate their location with GPS-quality accuracy without ever resurfacing. More importantly, these features will enable long-term autonomous navigation and safe recovery of underwater robots without the need for dedicated surface vessels for acoustic guidance. Overall, the outcomes of this project will contribute to the long-term marine ecosystem monitoring and ocean climate observatory research as well as in remote stealth mission execution for defense applications.This project will advocate a novel solution to the foundational problem of underwater robot localization and navigation by introducing the notion of 'optical homing and penning'. This new optics-based framework will incorporate the scientific and engineering concepts for active robot localization and non-invasive navigation without compromising the stealth. The integrated research will develop three sets of novel technologies for (i) distant UUV (Unmanned Underwater Vehicle) positioning with blue-green laser speckles, (ii) accurate 3D orientation measurements from coded bokeh spectrums, and (iii) GPS-quality pose estimates by a directionally-controlled adaptive LIDAR. The combined optical sensory system will be deployable from specialized buoys acting as floating lighthouses. An intelligent visual SLAM system will also be developed for robust state estimation in deep waters when no lighthouse beacons are visible. Additionally, a ROS (Robot Operating System)-based simulator will be developed for evaluating UUV navigation and mission execution performance. For feasibility analysis and assessment, this project will formalize real-world deployment strategies on two UUV platforms through comprehensive ocean trials in the northern Gulf of Mexico and the Atlantic Ocean. These research activities will be complemented by (i) curricula development for three STEM courses, (ii) undergraduate robotics team mentoring programs, and (iii) women in robotics workshop initiatives at UF.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.

对于自主水下机器人来说，能够长时间工作然后安全返回是一系列重要应用的关键特征，如水下检查、远程监视和季节性监测。在这种长期任务中，机器人面临的一大挑战是准确估计其位置，因为GPS信号无法穿透海面，而且水下没有Wi-Fi或无线电通信基础设施。使用专用的水面船只进行声学参考或浮出水面接收GPS信号都是耗电、计算昂贵的，而且通常是不可能的(在隐形应用中)。该项目将通过使用一种新的基于光学的框架和车载人工智能技术来解决这一问题，从而在科学和工程上取得进展。这些算法和系统将允许水下机器人以GPS质量的精度估计自己的位置，而不需要重新浮出水面。更重要的是，这些功能将使水下机器人能够长期自主导航和安全回收，而不需要专门的水面船只进行声学制导。总体而言，该项目的成果将有助于长期的海洋生态系统监测和海洋气候观测站的研究，以及用于国防应用的远程隐形任务执行。该项目将提出一种新的解决水下机器人定位和导航的基本问题的方案，通过引入“光学寻的和笔”的概念。这一新的基于光学的框架将融合主动机器人定位和非侵入性导航的科学和工程概念，而不会影响隐蔽性。这项综合研究将开发三套新技术，用于(I)利用蓝绿激光散斑进行远距离UUV(无人水下航行器)定位，(Ii)根据编码波克谱进行精确的3D方位测量，以及(Iii)利用定向控制的自适应激光雷达进行GPS质量的位姿估计。组合的光学传感系统将可以从充当漂浮灯塔的专门浮标上部署。还将开发一种智能视觉SLAM系统，在看不到灯塔信标的情况下，在深水中进行稳健的状态估计。此外，还将开发一个基于ROS(机器人操作系统)的模拟器，用于评估UUV导航和任务执行性能。为了可行性分析和评估，该项目将通过在墨西哥湾北部和大西洋进行综合海洋试验，在两个UUV平台上正式确定现实世界的部署战略。这些研究活动将得到(I)三门STEM课程的课程开发，(Ii)本科生机器人团队指导计划，以及(Iii)UF机器人研讨会倡议中的女性的补充。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。