AUV path planning for coverage search of static target in ocean environment. (1st December 2021) - Yao, Peng
Abstract: Aiming at the path planning problem for searching static target by autonomous underwater vehicles (AUVs) in ocean environment, this paper proposes a hierarchical method based on the maximum cumulative detection reward or search efficiency. First, the mission sea region is described in the form of target probability map, and the subregions with high search value are extracted by the method of expectation-maximization (EM). For multiple AUVs, we propose the bidirectional negotiation with biased min-consensus (BN-BMC) algorithm to determine the allocation and prioritization of subregions to be searched. On this basis, we utilize an adaptive oval spiral coverage (AOSC) strategy to plan the coverage path within each subregion, and take the Dubins path satisfying the AUV kinematic constraint as the transition path between subregions. Finally, the simulation results validate the advantage of our method. Highlights: This paper proposes a hierarchical method to solve the AUV path planning problem for target search in ocean environment. The bidirectional negotiation with biased min-consensus (BN-BMC) theory is proposed to allocate and prioritize subregions. The adaptive oval spiral coverage (AOSC) strategy is used to achieve the full coverage of an oval-shape subregion.