This paper presents the ongoing research activities of the Italian Interuniversity Center of Integrated Systems for the Marine Environment, ISME, in the field of harbour protection with autonomous marine vehicles. In particular, two different strategies have been developed in the recent years and have been extensively tested both in numerical simulations and in scale experiments. In the first case, a set of vehicles is positioned around an asset to be protected on the base of an optimization process of two cost functions, namely, the maximization of minimum interception distance and the minimization of maximum interception time. When an intruder is detected, an on-line optimization process selects, among the different vehicles, the one that exhibits the lowest estimated time to the menace. A motion planning algorithm with real-time obstacle avoidance is then used to drive the vehicle toward the intruder. In the second case, a team of vehicles is required to dynamically patrol a certain region by means of a decentralized control approach. The proposed solution is based on the merging of two concepts, the Voronoi tessellations and the Gaussian processes, and it allows robustness with respect to events as temporary communication or vehicle losses. It also exhibits characteristics of flexibility/scalability with respect to the number of team-mates.

Harbour Protection Strategies with Multiple Autonomous Marine Vehicles

MARINO, Alessandro;
2014

Abstract

This paper presents the ongoing research activities of the Italian Interuniversity Center of Integrated Systems for the Marine Environment, ISME, in the field of harbour protection with autonomous marine vehicles. In particular, two different strategies have been developed in the recent years and have been extensively tested both in numerical simulations and in scale experiments. In the first case, a set of vehicles is positioned around an asset to be protected on the base of an optimization process of two cost functions, namely, the maximization of minimum interception distance and the minimization of maximum interception time. When an intruder is detected, an on-line optimization process selects, among the different vehicles, the one that exhibits the lowest estimated time to the menace. A motion planning algorithm with real-time obstacle avoidance is then used to drive the vehicle toward the intruder. In the second case, a team of vehicles is required to dynamically patrol a certain region by means of a decentralized control approach. The proposed solution is based on the merging of two concepts, the Voronoi tessellations and the Gaussian processes, and it allows robustness with respect to events as temporary communication or vehicle losses. It also exhibits characteristics of flexibility/scalability with respect to the number of team-mates.
9783319138220
978-3-319-13823-7
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11386/4578460
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