基于遗传模拟退火算法的无人机航迹规划

航迹规划技术是无人机任务规划系统中重要的核心技术之一,无人机飞行空间广阔,需要一种快速搜索最佳路径的方法.首先在飞行区域中建立数字地图模型和防空威胁区模型,在满足无人机飞行约束条件的情况下,为无人机航迹规划提供一种遗传模拟退火算法,充分利用模拟退化算法的概率突跳特性和遗传算法强大的快速搜索能力.仿真结果表明,使用该算法无人机能够自动避开模拟数字地图的威胁区,搜索出一条安全有效航迹,并保证航线的完整性和最优性.

UAV route planning based on the genetic simulated annealing algorithm

Path planning technology is one of the core technologies of UAV mission planning system. UAV flight space is large, which needs a method to quickly find out the best path. This paper sets up a digital map model and a model for air defense threat area in the airfield domain. Under the condition of meeting the UAV flight constraints, the paper provides a genetic simulated annealing algorithm for UAV track planning, and makes full use of the probability kick features of simulation degradation algorithm and powerful ability of fast searching genetic algorithm. Simulation results show that with this algorithm, UAV can automatically avoid the threatened field of simulated digital map area, search out a safe and effective path, and ensure the integrity and optimality of their routes.