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A side-scan sonar data-driven coverage planning and tracking framework
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DOI：10.1016/j.arcontrol.2018.10.012.png)
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Abstract
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Mapping an unknown large-scale marine area by a side-scan sonar onboard a marine vehicle as quickly as possible is often of great importance. It is also important that a-priori unknown interesting parts of the area are scanned in more detail, i.e. with the removal of sonic shadows. In contrast to the standard overlap-all-sonar-ranges lawnmower pattern offline static coverage problem solution for side-scan sonar missions, here a novel online side-scan sonar data-driven coverage solution is proposed. The proposed coverage algorithm provides a coverage solution based on local information gain from side-scan sonar data. At the same time, the solution is generated in such a way that coverage path length/time is minimized while covering the same area as the standard lawnmower. Upper and lower bounds of the proposed algorithm's improvement compared to the overlap-all-sonar-ranges lawnmower method are estimated analytically and validated through extensive mission parameters variation simulations. Simulation results show that this approach can cut down coverage path length/time significantly compared to the standard lawnmower method in most application cases. (C) 2018 Elsevier Ltd. All rights reserved.
Keywords:
Autonomous underwater vehicles
Coverage path planning
Sensor data-driven coverage
Side-scan sonar
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