Aera coverage path planning for unmanned ships: an improved COA and PWO composite algorithm

Unmanned Surface Vehicle (USV) face challenges in underwater survey tasks, considering both environmental and self-performance constraints. In complex marine environments with obstacles, optimal route planning is crucial for survey efficiency. To address this issue, we propose an integrated approach by combining the traditional Grey Wolf Optimization (GVO) algorithm with the Coati Optimization Algorithm (COA), forming the COA-GWO composite algorithm, validated through simulation. Ultimately, by defining the objective function for underwater survey area coverage path planning (ACPP), effective path planning is achieved.