基于动态加权A~*算法的无人机航迹规划  

UAV route planning based on improved dynamic weighted A~* algorithm

作　　者：何燕[1] HE Yan(Tianhua College,Shanghai Normal University,Shanghai 201815,China)

机构地区：[1]上海师范大学天华学院,上海201815

出　　处：《河北科技大学学报》2018年第4期349-355,共7页Journal of Hebei University of Science and Technology

基　　金：上海市重大内涵项目(2016-SHNGE-05NH)

摘　　要：随着无人机航迹规划高维空间的扩展,无人机的飞行环境变得异常复杂,其外部威胁不再是简单的二维静态威胁,传统的蚁群算法和人工势场算法已经不能满足实时性和高复杂环境的要求。为解决上述问题,提出新的基于动态加权A*算法的无人机航迹规划。首先对无人机的飞行环境进行建模,通过研究航迹规划的转弯半径、航迹段长度和最大航程限制等约束条件,用于保证无人机的安全飞行,从而降低坠机率和威胁概率;其次,通过研究无人机的航迹和外部威胁参数,设计出新的航行方式,降低航行危险和减少损失;然后,通过扩展顶点势能定位和网格图整体变化的动态权重,获得动态环境下的代价函数,增加避障搜索速度、精度和加深回避程度。最后,通过仿真结果表明,在同一应用环境下,所提算法与蚁群算法和人工势场算法相比,航迹路径最优、威胁代价最小和算法执行的时间最短。综上,基于动态加权A*算法很好地应用于无人机航迹规划,降低了无人机航迹代价,缩短了算法完成时间,提高了复杂环境下无人机航迹规划的搜索速度和精度。With the expansion of high dimensional space in UAV trajectory planning,the flying environment of UAV is very complex,and the external threat of UAV is no longer a simple two-dimensional static threat.The traditional ant colony algorithm and artificial potential field algorithm cannot meet the requirements of real-time and high complex environment.To solve the above problems,a new dynamic programming algorithm based on dynamic weighted A*algorithm is proposed.Firstly,the flight environment of UAV is modeled.By studying the constraints such as the turning radius,the length of track section and the limit of the maximum range,the safe flight of UAV is ensured,thus reducing the crash rate and the threat probability.Secondly,a new navigation mode is designed by studying the track and external threat parameters of the UAV,which can reduce the danger of navigation and reduce the loss.Then,the potential energy of the vertex can be expanded.The dynamic weight of the overall change of location and grid graph is obtained,and the cost function in dynamic environment is obtained,which increases the speed,accuracy and evasion degree of obstacle avoidance search.Finally,the simulation results show that under the same application environment,the proposed algorithm has the best path,the least threat cost and the shortest execution time compared with the ant colony algorithm and artificial potential field algorithm.To sum up,the dynamic weighted A*algorithm can be well applied to UAV trajectory planning,reducing the cost of UAV track,shortening the completion time of the algorithm and improving the search speed and precision of unmanned aerial vehicle trajectory planning in complex environment.

关 键 词：机电一体化技术 无人机 航迹规划 动态加权 高维空间 复杂环境 A*算法 

分 类 号：TP13[自动化与计算机技术—控制理论与控制工程]