改进粒子群算法在三维航路规划中的应用

Route Planning in the Three-Dimensional Space Using Improved Adaptive PSO

为确保无人机安全地飞到任务执行地,对无人机航路规划在三维空间中的航路规划问题进行研究,并提出了基于禁忌搜索的自适应粒子群算法来解决此问题。粒子群算法有其快速性、随机性和收敛性。首先利用粒子群算法全空间地搜索最优解可能存在的区域,当算法接近最优解且粒子群算法过变慢时,采用禁忌搜索,利用其较强的"爬山"能力,克服PSO可能出现的早熟现象和局部收敛现象。

To ensure the Unmanned Aerial Vehicle （UAV）reaches the destination safely,the route planning of a UAV in the three- dimensional space is discussed,and adaptive particle swarm optimization based on taboo search is proposed. Particle Swarm Optimization （P SO）is fast,random and convergent. Firstly,P SO is used to search the whole space. And then,Taboo Search （TS）is introduced when the algorithm is close to the optimal solution and the speed of PSO comes down. In order to solve premature convergence and local convergence, TS is used because of its strong climbing ability.