Cooperative survey of seabed ROIs using multiple USVs with coverage path planning

Abstract

A fine-grained offshore seabed map is critical to the site selection and construction for offshore wind farms, which can be obtained by the cooperative survey with multiple unmanned surface vehicles (USVs). To accomplish the mission of surveying multiple regions of interest (ROIs) by cooperative coverage path planning of USVs, a sequential algorithm is proposed to facilitate the generating the ROIs’ boundary, decomposing concave polygons, and planning coverage path for multiple USVs. First, in order to extract the multiple ROIs and generate accurate polygon boundaries, the grid clustering method and the α -shapes method are adopted with a prior seabed distribution map information. Second, an improved Bayazit decomposition algorithm is presented to reduce the number of sub-regions and turnings by USVs during the coverage planning. Third, aiming at routing the traveling order of every sub-region, a novel discrete group teaching optimization algorithm with an adaptive neighborhood radius model is proposed, which performs robustly compared with five classical multiple traveling salesman algorithms. Finally, numerical simulation results show that the proposed algorithm integrating the ROIs determination and coverage path planning methods is effective for cooperative surveying of multiple USVs.