Abstract
After the 2010 Deepwater Horizon accident, environmental regulations shifted to a more goal-oriented approach that required risk management plans for controlling site-specific risks. The real-time long-term monitoring of spilled oil drifting behavior on the sea surface is essential for decreasing the risk to coastal environments posed by spilled oil. This paper describes an autonomous robotic platform or autonomous surface vehicle (ASV), propelled by wind and water currents for the long-term monitoring of spilled oil on the ocean surface. This paper also describes a sensor-based guidance, navigation, and control system for oil spill tracking by ASV in unsteady and uncertain environments. This paper makes a unique contribution to the literature in proposing a cluster-based decision-making algorithm for sailing the ASV based on a complete scanning history of the area surrounding the vehicle by the oil detection sensor. A Gaussian-based oil cluster filtering algorithm is introduced to identify the largest oil slick patch. The physical constraints of the ASV have been taken into account to allow for the computation of feasible maneuvering headings for sailing to avoid sailing upwind (i.e., in the direction from which the wind is coming). Finally, using neoprene sheets to simulate oil spills, field test experiments are described to validate the operation of the ASV with respect to oil spill tracking using a guidance, navigation, and control system based on onboard sensor data for tracking the artificial oil targets.
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Rathour, S.S., Kato, N., Senga, H., Tanabe, T., Yoshie, M., Tanaka, T. (2017). Development of a Robotic Floating Buoy for Autonomously Tracking Oil Slicks Drifting on the Sea Surface (SOTAB-II): Experimental Results. In: Kato, N. (eds) Applications to Marine Disaster Prevention. Springer, Tokyo. https://doi.org/10.1007/978-4-431-55991-7_4
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DOI: https://doi.org/10.1007/978-4-431-55991-7_4
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