S&AS: INT: COLLAB: Goal-driven Marine Autonomy with Application to Fisheries Science and Management

点击翻译按钮获取中文摘要

Marine robots can be used to accurately map and track marine life, leading to a better interpretation of variability and migration patterns that are important to fisheries managers in marine protected areas (MPAs). Principles of engineering and oceanography can be used to maximize the impact of a network of marine robots, but because fisheries managers, oceanographers, and roboticists have different perspectives and knowledge bases, it can be difficult to take advantage of cutting-edge research in each field without significant effort to translate among the groups. Researchers will develop a computational interface that translates human-specified missions of fisheries managers into multi-level planning for a fleet of marine robots to monitor fish populations in a dynamic coastal ocean environment. The system will be designed with input from fisheries managers through a series of workshops, and will be field-tested at Gray's Reef National Marine Sanctuary, a federally-managed MPA off the coast of Georgia. The research will lead to more accurate and effective ways to monitor fish populations in MPAs, as well as breakthroughs in key areas of artificial intelligence and autonomous systems. Many of the results will be applicable to other smart and autonomous systems in challenging environments. In addition, the project will train graduate students and broaden undergraduate education in Science, Technology, Engineering, and Mathematics (STEM), and offer a number of outreach activities, including working with the University of Georgia Marine Extension service to develop a summer camp for middle and high school students.The project is focused on developing an intelligent physical system (IPS) that consists of a heterogeneous fleet of marine robots, cooperatively tracking fish movement and surveying the habitat with minimum request for human intervention. The IPS will translate the human-specified missions of fisheries managers into goal-driven task designs for each robot, and automatically generate executable plans for the networked mobile sensing agents. The system will autonomously and persistently collect in-situ measurements and acoustic detections of fish species while maintaining multi-scale data streams and constructing multiple spatial-temporal maps reflecting the conditions of the ecosystem. The research aims to discover the hotspots (e.g., spatial locations with sustained congregations of fish), as well as illuminate more information about how and when fish move among these hotspots. This goal is quite challenging due to a number of gaps between project needs and the state-of-art autonomy research. Researchers will address the challenges through new developments that accomplish three main tasks: (1) Developing the goal-driven marine autonomy for fish habitat survey, (2) realizing the goal-driven autonomy on physical systems, and (3) evaluating the developed framework through real-life field work, experiments, and data analysis.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.