The paper investigates the problem of path planning techniques for multi-copter uncrewed aerial vehicles (UAV) cooperation in a formation shape to examine surrounding surfaces. We first describe the problem as a joint objective cost for planning a path of the formation centroid working in a complicated space. The path planning algorithm, named the generalized particle swarm optimization algorithm, is then presented to construct an optimal, flyable path while avoiding obstacles and ensuring the flying mission requirements. A path-development scheme is then incorporated to generate a relevant path for each drone to maintain its position in the formation configuration. Simulation, comparison, and experiments have been conducted to verify the proposed approach. Results show the feasibility of the proposed path-planning algorithm with GEPSO.

翻译：本文研究了多旋翼无人机以编队形式协同探测周边表面时的路径规划技术。我们首先将该问题描述为在复杂空间中规划编队质心路径的联合目标代价函数。随后，提出一种名为广义粒子群优化的路径规划算法，用于构建在规避障碍物同时满足飞行任务要求的最优可飞行路径。通过引入路径展开方案，为编队中每架无人机生成保持其队形位置的对应路径。研究通过仿真、对比与实验验证了所提方法。结果表明，采用广义粒子群优化的路径规划算法具有可行性。