Path planning for an autonomous underwater vehicle in a cluttered underwater environment based on the heat method

This paper proposes a novel autonomous underwater vehicle path planning algorithm in a cluttered underwater environment based on the heat method. The algorithm calculates the isotropic and anisotropic geodesic distances by adding the direction and magnitude of the currents to the heat method, which is named the anisotropy-based heat method. Taking account of the relevant influence of the environment on the cost functions, such as currents, obstacles and turn of the vehicle, an efficient collision-free and energy-optimized path solution can be obtained. Simulation results show that the anisotropy-based heat method is able to find a good trajectory in both static and dynamic clutter fields (including uncertain obstacles and changing currents). Compared with the fast marching (FM) algorithm, the anisotropy-based heat method is not only robust, flexible, and simple to implement, but it also greatly saves time consumption and memory footprint in a time-variant environment. Finally, the evaluation criteria of paths are proposed in terms of length, arrival time, energy consumption, and smoothness.