摘要
研究基于粒子群算法的无人机灭火路径规划仿真方法,高效获得最优灭火路径,为无人机快速无碰撞灭火提供保障。以现实灭火环境为依据构建无人机灭火路径规划仿真环境模型,结合灭火路径长度代价、障碍危险代价、无人机航迹高程及水平转角代价建立适应度函数;通过细菌觅食算法改进基础粒子群算法,获得改进粒子群算法,定位检测出灭火环境中的火点位置,并以此类火点位置作为规划的目标点,仿真环境中提取的原始点作为起点,由若干条路径构成粒子种群,通过改进粒子群算法在仿真环境中运用适应度函数实现粒子种群的迭代寻优,获得最优无人机灭火路径。结果表明,上述方法可实现不同起点与火点间的最优无人机灭火路径规划,规划时收敛速度高,所规划的无人机灭火路径长度短,可与障碍物及危险体具备足够安全间距,且水平转角平滑,可满足无人机的高效无碰撞灭火需求,整体规划效果理想。
The simulation method of UAV fire extinguishing path planning based on particle swarm optimization algorithm was studied in the paper to obtain the optimal fire extinguishing path efficiently and provide guarantee for uav fast collision free fire extinguishing.Based on the actual fire-fighting environment,a simulation environment model for UAV fire-fighting path planning was built,and a fitness function was established by combining the firefighting path length cost,obstacle danger cost,UAV track elevation and horizontal angle cost.By improving the basic particle swarm optimization algorithm through the bacterial foraging algorithm,the improved particle swarm optimization algorithm was obtained to locate and detect the location of fire points in the fire extinguishing environment,and the location of such fire points was taken as the target point of planning,the original point extracted from the simulation environment was taken as the starting point,and the particle population was formed by several paths.The improved particle swarm optimization algorithm was used to optimize the particle population iteratively by fitness function in simulation environment,and the optimal fire extinguishing path of UAV was obtained.Results show that this method can realize optimal UAV fire extinguishing path planning between different starting points and fire points.When planning,the Rate of convergence is high,the length of the planned UAV fire extinguishing path is short,it can have sufficient safety distance from obstacles and dangerous bodies,and the horizontal corner is smooth,which can meet the efficient and collision free fire extinguishing needs of UAVs.The overall planning effect is ideal.
作者
李锐君
董素鸽
LI Rui-jun;DONG Su-ge(School of Telecommunications and Intelligent Manufacturing,Zhengzhou Sias University,Zhengzhou Henan 451150,China;School of Information and System Engineering,Information Engineering University,Zhengzhou,Henan 450000,China)
出处
《计算机仿真》
北大核心
2023年第9期43-48,共6页
Computer Simulation
基金
河南省科技攻关项目(NO.232102221029)
河南省科技攻关项目(NO.212102210150)
河南省2022年民办普通高等学校学科专业建设项目(教办政法[2021]255号)。
关键词
粒子群优化
无人机
灭火路径规划
仿真环境模型
适应度函数
细菌觅食算法
Particle swarm optimization
Unmanned aerial vehicle(UAV)
Fire extinguishing path planning
Simulation environment model
Fitness function
Bacterial foraging algorithm
