Environment-informed 3D path planning for autonomous underwater vehicles in ocean current fields

Turbulent ocean vortices create complex and highly uncertain environments for autonomous underwater vehicles (AUVs), making three-dimensional path planning essential for mission execution. To enhance the mission efficiency and navigational safety of AUV operations in such dynamic ocean conditions, an ocean-current-aware particle swarm optimization (OCPSO) algorithm is proposed. To accurately represent underwater flow conditions, a three-dimensional ocean current field model is first created. Subsequently, a 3D path planning model is developed by carefully taking terrain restrictions, path length, and current-induced energy consumption into account. Finally, an ocean-current-aware particle swarm optimization algorithm is developed to enable effective adaptation to underwater current dynamics. Experimental results demonstrate that the proposed algorithm improves solution quality, robustness, and overall fitness performance in the considered simulation settings.