NRI: Enhancing Autonomous Underwater Robot Perception for Aquatic Species Management

水下领域几乎占据了地球的五分之四，对人类福祉、生态平衡以及相应的社会经济繁荣具有重大影响。然而，它给自主系统的探索带来了巨大的挑战，特别是在感知和定位能力方面。许多应用，例如在环境监测和生态系统保护方面，将大大受益于使用自动水下机器人(AUV)，从而提高效率、生产率和安全性。特别是，保护水下生态系统对于维持适当的生态平衡极为重要，这是一项重要的工作，在这种情况下，自主水下系统可以成为宝贵的工具。该项目将整合机器人学和海洋保护生物学方面的专业知识，为自主水下机器人感知和导航创造新的能力，使机器人能够识别、跟踪和定位水生物种。研究团队将在一个负担得起的开源自主机器人平台上整合机器人视觉、学习和本地化方面的理论进步，使用现场试验、出版物、软件、设计和数据集发布，以及会议中的教程和研讨会。研究小组还将把研究成果纳入课程课程，以更好地为学生在机器人和智能系统方面的工作做好准备，同时促进保护生物学的知识。调查人员将特别注意从代表性不足的群体中招募学生加入研究团队。该项目将整合机器人学和海洋保护生物学方面的专业知识，为自主水下机器人感知和导航创造新的能力，使机器人能够识别、跟踪和定位水生物种。这项研究将使AUV能够在沿海栖息地充当有效的机器人助手来管理这些生态系统。具体地说，研究人员将创造方法来(1)增强专门用于稳健检测水生物种的多模式水下图像，(2)使用零和/或一次射击学习来识别有限的训练图像中的水生物种，以及(3)结合声学和水深测量方法来准确地定位水下机器人。研究成果将在适当的现场地点单独或作为一个集成的、连贯的水下机器人系统进行评估。研究人员在水下机器人和水生态方面拥有互补的专业知识。研究团队拥有的各种专业知识的整合将导致水下自主机器人技术的重大进步，并使AUV能够在具有重大生态和经济重要性的领域使用。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。

The underwater domain takes up almost four-fifths of the planet and has significant bearing on human well-being, ecological balance, and accordingly, socio-economic prosperity. However, it poses significant challenges to exploration by autonomous systems, particularly in perception and localization capabilities. Many applications, e.g., in environmental monitoring and ecosystem preservation, would benefit significantly from using autonomous underwater vehicles (AUVs), with improved efficiency, productivity, and safety. In particular, the preservation of the underwater ecosystem is of utmost importance in maintaining proper ecological balance and is a significant undertaking where autonomous underwater systems can be valuable tools. This project will integrate expertise in robotics and marine conservation biology to create novel capabilities for autonomous underwater robotic perception and navigation which will make it possible for robots to identify, track, and localize aquatic species. The research team will integrate theoretical advances in robot vision, learning, and localization on an affordable, open-source autonomous robotic platform using field trials, publications, software, and design and dataset releases, in addition to tutorials and workshops in conferences. The research team will also incorporate research results into course curricula to better prepare students for jobs in robotics and intelligent systems while advancing knowledge in conservation biology. The investigators will pay particular attention to recruit students from underrepresented groups to the research team. This project will integrate expertise in robotics and marine conservation biology to create novel capabilities for autonomous underwater robotic perception and navigation which will make it possible for robots to identify, track, and localize aquatic species. This research will enable AUVs to act as effective robotic assistants in littoral habitats to manage these ecosystems. Specifically, the investigators will create methods to (1) enhance multimodal underwater imagery specifically for robust detection of aquatic species, (2) use zero- and/or one-shot learning for identifying aquatic species with limited training imagery, and (3) combine acoustic and bathymetric methods for accurate underwater robot localization. The research outcomes will be evaluated both individually and as an integrated, coherent system onboard underwater vehicles at appropriate field locations. Investigators have complementary expertise in underwater robotics and aquatic ecology. The integration of the diverse expertise possessed by the research team will lead to major advances in underwater autonomous robotics and enable the use of AUVs in a domain of significant ecological and economic importance.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.