Three-Dimensional Underwater Path Planning Based on Modified Wolf Pack Algorithm

Abstract

Path planning is an important problem in autonomous control technology. This paper aims to overcome the shortcomings of the wolf pack algorithm (WPA), such as slow rate of convergence and low convergence precision, by improving the three intelligent behaviors of the WPA, namely, scouting, summoning, and beleaguering. To improve the scouting behavior, interactive scouting is proposed to increase the interactivity among wolf pack. Furthermore, to improve the summoning behavior, a prey-based adaptive step model is established to improve the searching ability. Finally, calculation rules of new beleaguering behavior are designed, which enhance the local fine search ability considerably. A fast path planning method based on dubins path was proposed, which applied the dubins path planning to meet angle control constraint and tunes the turning radius to meet control constraint. The dubins path planning method based on the modified WPA is proposed by establishing the underwater environment threat model under the condition of autonomous underwater vehicle constraint. The path between the path points is the shortest, the threat is minimal, and the energy consumption is the least without the consideration of ocean current. Simulation results show that the modified WPA has a high rate of convergence and good local search capability in the high-precision, high-dimensional, and multi-peak function; moreover, it does not converge prematurely.