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，可以长时间操作，然后安全地返回是一系列重要应用程序的关键功能，例如海底检查，远程监视和季节性监控。在这样的长期任务中，机器人的一个主要挑战是要准确估算其位置，因为GPS信号无法渗透到海洋的表面，并且在水下没有Wi-Fi或无线电通信基础设施。使用专用的表面容器进行声学参考或进入GPS信号的水面是饥饿的，计算昂贵的，并且通常是不可能的（在隐形应用中）。该项目将通过使用基于光学的框架和板载AI技术来解决此问题，从而实现科学和工程的进步。这些算法和系统将允许水下机器人以GPS质量的准确性估算其位置，而无需重新铺面。更重要的是，这些功能将使长期自主导航和安全恢复水下机器人的安全恢复，而无需专用的表面vissels进行声学指导。总体而言，该项目的结果将有助于长期海洋生态系统监测和海洋气候观察研究以及对国防应用的远程隐身任务执行。该项目将通过引入'Optical Housing and Penning的概念来提倡一个新的解决方案，以解决水下机器人本地化和导航的基础问题。这个新的基于光学的框架将结合主动机器人本地化和非侵入性导航的科学和工程概念，而不会损害隐身。综合研究将开发三组新技术，用于（i）遥远的UUV（无人驾驶的水下车辆）定位，（（ii）从编码的Bokeh Spectrums和（iii）GPS极端姿势估算的准确3D方向测量值通过方向控制的适应性lidar估计。合并的光学感觉系统将可以从充当浮动灯塔的专用浮标中部署。当看不到灯塔信标时，还将开发一个智能的视觉大满贯系统，以在深水中进行稳健的状态估计。此外，将开发基于ROS（机器人操作系统）的模拟器来评估UUV导航和任务执行性能。为了进行可行性分析和评估，该项目将通过墨西哥北部和大西洋北部的全面海洋试验在两个UUV平台上的现实部署策略形式化。这些研究活动将由（i）三个STEM课程的课程开发完成，（ii）本科机器人团队心理计划，以及（iii）在UF.Robotics研讨会上的女性，该奖项反映了NSF的法定任务，并通过该基金会的知识优点和广泛的影响来评估NSF的法定任务，并被认为是通过评估值得的。