摘要
主要讨论了有障碍区的多无人机多目标点的路径规划问题.采用Dubins模型满足无人机的曲率约束,建立了含有混合变量的多约束优化问题,通过改进的遗传算法对优化问题进行求解,得到了满足基本约束条件的无人机遍历顺序和航向角,并确定了每个无人机的Dubins路径;给出了确定路径进入障碍区的检测方法,采用Dubins-快速扩展随机树算法对进入障碍区域的路径进行调优,得到了满足障碍约束条件的优化无人机路径.通过仿真算例对比实验,证明了所提算法的有效性.
The problem of path planning of multiple unmanned aerial vehicles(UAVs)and multiple target points within the obstacle area is talked about in this paper.By using the Dubins model,the curvature constraint of the UAV is satisfied.A multi-constraint optimization problem with mixed variables is established.The optimization problem is solved by an improved genetic algorithm(IGA).A detection method to determine the path which enters the obstacle region is presented.The Dubins-rapidly exploring random tree(RRT)algorithm is used to tune the path which enters the obstacle region,and an optimized UAV path satisfying the obstacle constraint is obtained.The effectiveness of the proposed algorithm is proved via the comparison of simulation examples.
作者
肖春晖
邹媛媛
李少远
XIAO Chunhui;ZOU Yuanyuan;LI Shaoyuan(Department of Automation,Shanghai Jiao Tong University,Shanghai 200240,China;Key Laboratory of System Control and Information Processing,Ministry of Education of China,Shanghai 200240,China)
出处
《空间控制技术与应用》
CSCD
北大核心
2019年第4期46-52,共7页
Aerospace Control and Application
基金
国家自然科学基金资助项目(61773162,61833012)~~
关键词
曲率约束
障碍区域
多目标点路径规划
遗传算法
curvature constraint
obstacle area
multi-target point path planning
genetic algorithm
