Underwater gliders have revealed as a valuable scientific platform, with a growing number of successful environmental sampling applications. They are specially suited for long range missions due to their unmatched autonomy level, although their low surge speed make them strongly affected by ocean currents. Path planning constitute a real concern for this type of vehicle, as it may reduce the time taken to reach a given waypoint or save power. In such a dynamic environment it is not easy to find an optimal solution or any such requires large computational resources. In this paper, we present a path planning scheme with low computational cost for this kind of underwater vehicle that allows static or dynamic obstacle avoidance, frequently demanded in coastal environments, with land areas, strong currents, shipping routes, etc. The method combines an initialization phase, inspired by a variant of the A* search process and ND algorithm, with an optimization process that embraces the physical vehicle motion pattern. Consequently, our method simulates a glider affected by the ocean currents, while it looks for the path that optimized a given objective. The method is easy to configure and adapt to various optimization problems, including missions in different operational scenarios. This planner shows promising results in realistic simulations, including ocean currents that vary considerably in time, and provides a superior performance over other approaches that are compared in this paper.
Path planning; Underwater gliders; Obstacle avoidance