With the aim of aiding mitigation efforts, in mapping and simulating the transport of the discharged hydrocarbon this paper proposes an autonomous surface vehicle (ASV), propelled by wind and water currents for the long-term monitoring of spilled oil on the ocean surface. 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 in 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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