摘要
针对快递无人机在复杂城镇环境条件下的路径寻优问题,提出了一种基于A^*和鸽群算法的航路规划算法。首先,建立威胁代价和障碍物模型,利用约束条件缩短A^*算法搜索时间,再通过A^*算法引导无人机快速到达目标点;然后,对鸽群的粒子编码方式和适应度函数计算方法进行改进,通过鸽群优化算法实现障碍物的规避;最后,利用三次B样条曲线对航路进行平滑化和重规划。仿真结果表明,该算法收敛速度快、航路长度短、威胁代价小,生成的航迹平滑可飞,适合快递无人机在复杂城镇环境中穿行。
For route optimization requirements of delivery UAV in complex urban environment,an route planning algorithm based on A^*and pigeon swarm algorithm was proposed.First,a model of threat cost and obstacle was built,constraint conditions was used to shorten the search time,the UAV was guided to the target point quickly by A^*algorithm.Then,the particles coding method of pigeon swarm and the calculation method of pigeon swarm fitness function were improved,pigeon swarm algorithm was used to avoid obstacles.Finally,the cubic B-spline curve was used to smooth and replan the planned route.Simulation results indicate that the algorithm has a fast convergence speed,a short route length,a low threat cost,and the track is smooth,thus ensuring the safety of UAV in complex town environment.
作者
刘昂
蒋近
许迪文
LIU Ang;JIANG Jin;XU Diwen(College of Information Engineering,Xiangtan University,Xiangtan 411105,China)
出处
《飞行力学》
CSCD
北大核心
2020年第3期34-40,51,共8页
Flight Dynamics
