Cyber-Maritime Cycle: Autonomy of Marine Robots for Ocean Sensing

Marine robots are playing important roles in environmental sensing andocean observation applications. This tutorial introduces the overall systemsarchitecture and patterns for data streams that enable autonomyfor marine robots in environmental sensing applications. The articleproposes the concept of cyber-maritime cycle and surveys its use as arecent development in marine robotics. Supported by communicationnetworks, autonomy can be achieved using at least three feedback loopsin a cyber-maritime cycle, each running at different time scales or temporalfrequencies. When information is circulating around the cycle, itis transformed between two representations: the Lagrangian view andthe Eulerian view. Important functional blocks, such as mission planning,path planning, data assimilation, and data-driven modeling arediscussed as providing conversions between the two views of data. Thetutorial starts with an overview of enabling technologies in sensing,navigation, and communication for marine robotics. The design of experimentmethod is then reviewed to plan optimal sensing locations forthe robots. The tutorial discusses a class of path planning methods thatproduces desired trajectories of marine robots while combating oceancurrent. The lack of an accurate Eulerian map for ocean current willlead to tracking error when robots attempt to follow the planned pathsto collect Lagrangian data. The performance of robot navigation can beevaluated through the controlled Lagrangian particle tracking method,which computes trends and bounds for the growth of the tracking error.To improve the accuracy of the Eulerian map of ocean current, adata-driven modeling approach is adopted. Data assimilation methodsare leveraged to convert Lagrangian data into Eulerian map. In addition,the spatial and temporal resolution of Eulerian data maps canbe further improved by the motion tomography method. This tutorialgives a comprehensive view of data streams and major functional blocksunderlying autonomy of marine robots.

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