Research on Path Planning for Unnamed Wing-in-Ground Craft Based on Improved Sparrow Search Algorithm-Grey Wolf Optimizer Hybrid Algorithm

Leveraging its exceptional ultra-low altitude flight capability and high economic effi-ciency, the unnamed Wing-in-Ground (WIG) craft offers unique advantages in mari-time missions such as island patrol and rapid replenishment. However, the path plan-ning for unnamed WIG crafts faces the dual challenge of precise obstacle avoidance and ultra-low altitude maintenance, due to the obstacle distribution in island regions and the altitude window constraints inherent to ground effect flight. To address this, this paper proposes a path planning method based on an improved hybrid Sparrow Search Algorithm and Grey Wolf Optimizer. This method integrates the swarm intel-ligence of the Sparrow Search Algorithm, employs a self-destruction mechanism to es-cape local optima. Furthermore, it combines the hierarchical guidance of the Grey Wolf Optimizer to enhance convergence accuracy. The algorithm integrates ground-effect maintenance constraints and a reef threat model, and smooths the final path using cubic B-spline curves. Simulation results demonstrate that the proposed algorithm outperforms the standard Sparrow Search Algorithm, Grey Wolf Optimizer, and Particle Swarm Optimization in terms of convergence speed, optimization accu-racy, and obstacle avoidance success rate. It is capable of generating a feasible, safe, and smooth path, thereby supporting the autonomous navigation of unmanned WIG crafts in island reef waters.