基于Voronoi图和动态自适应蚁群算法的UAV航迹规划

Route Planning of UAV Based on Voronoi Diagram and Dynamic and Adaptive Ant colony algorithm[HS)]

摘要:

以UAV航迹规划为应用背景,提出了一种基于Voronoi图和动态自适应蚁群算法的航迹规划方法;为了提高航迹规划问题最优解的质量及全局求解能力,克服传统蚁群算法收敛速度慢、容易陷入局部最优等缺点,提出了一种动态自适应蚁群算法;采用动态自适应航迹点选择策略并将信息素更新规则和挥发系数进行动态自适应调整变化来对蚁群算法进行了改进,提高了算法的求解效率;根据战场已知威胁源生成Voronoi加权图,并与所提的动态自适应蚁群算法相结合求解规划空间中的最优航迹;考虑到UAV的物理约束限制,对生成的可行航迹进行平滑优化;仿真结果表明,该方法能够为UAV规划出一条满足要求的可飞航迹,验证了所提方法在解决航迹规划问题时是可行、有效的;

Abstract:

In the application background of UAV route planning,a method based on Voronoi diagram and dynamic and adaptive ant colony algorithm is proposed for route planning of UAV.In order to improve the quality of the optimal solution and the ability in searching the whole best solution of the path planning problem,and overcome the shortcomings of the traditional ant colony algorithm,such as premature convergence,in local optimum and running slowly,a dynamic and adaptive ant colony algorithm is proposed.A dynamic adaptive track point selection strategy,and a updating for pheromone and volatilization coefficient dynamically are used to improve the solution efficiency of the algorithm.The weighted Voronoi diagram is created according to the certain threat sources,with the dynamic and adaptive ant colony algorithm to search the optimal path in the space.Considering the physical constraints restrict of UAV,a route smoothing method is used to optimize the feasible path.Simulation results show that the proposed method can meet the requirements for route planning of UAV.Through the simulation,the feasibility and effectively of the scheme are verified.