摘要
针对无人机(unmanned aerial vehicle,UAV)在存在多种威胁的三维环境下的安全路径规划问题,提出了一种改进的混沌粒子群优化增强算法(improvedchaotic,velocityand nonlinear decreasing inertia weight particle swarm optimization,IC-VANDIWPSO)。首先,建立一个具有地形约束和无人机性能约束的威胁环境模型,把路径规划问题转化为成本函数的优化问题。再利用IC-VANDIWPSO算法与约束的对应关系,高效搜索复杂的环境,找到安全性高且成本函数小的最优路径。仿真结果表明,IC-VANDIWPSO算法在收敛速度、初始化时间、路径平滑性以及稳定性等方面都具有显著的优势,获得了更优的路径。
For the safe path planning of UAVs in a three-dimensional environment with multiple threats,an improved chaotic particle swarm optimization enhancement algorithm(Improved Chaotic Velocity,and Nonlinear Decreasing Inertia Weight Particle Swarm Optimization Algorithm,IC-VANDIWPSO)is proposed.Firstly,a threat environment model with terrain constraints and UAV performance constraints is established,and the path planning problem is transformed into an optimization problem of the cost function.Then,by using the corresponding relationship between IC-VANDIWPSO algorithm and constraints,the complex environment can be efficiently searched and the optimal path with high security and small cost function can be found.Finally,according to the simulation results,IC-VANDIWPSO algorithm has obvious advantages in convergence speed,initialization time,path smoothness and stability,and obtains a better path.
作者
褚宏悦
易军凯
CHU Hongyue;YI Junkai(School of Automation,Beijing Information Science and Technology University,Beijing 100192,China)
出处
《控制工程》
CSCD
北大核心
2024年第6期1027-1034,共8页
Control Engineering of China
基金
国家自然科学基金资助项目(U1636208)。
关键词
无人机
路径规划
粒子群优化增强
非线性递减惯性权重
混沌理论
Unmanned aerial vehicle
route planning
particle swarm optimization enhancement
nonlinear decreasing inertial weight
chaos theory
