基于某种生物启发式算法的无人机航迹规划

Path Planning of UAV Based on a Biological Heuristic Algorithm

无人机航迹规划问题是无人机实现自主飞行的重点和难点,本文提出了一种基于海洋生物启发式的算法,并将其应用于无人机航迹规划中。首先对飞行过程中的约束条件与威胁环境进行分析与建模,使用合适的规划空间方法,将种群初始化,根据位置更新策略不断进行种群迭代,使种群逐渐向最优解进化。仿真实验表明,该算法可有效提高全局搜索能力,避免陷入局部最优解,算法具有快速收敛和可靠性的特点,为无人机航迹规划研究提供了新思路。

Path planning is the difficult issue for UAV to achieve autonomous flight.An algorithm based on Marine biological heuristic was proposed and applied to UAV path planning.Firstly,the constraints and threat environment in the flight process were analyzed and modeled,the population was initialized by using the appropriate planning space method,and the population iteration was continuously performed according to the location update strategy to make the population gradually evolve to the optimal solution.The simulation results show that the algorithm can effectively improve the global search ability and avoid falling into the local optimal solution.The algorithm has the characteristics of fast convergence and reliability,and provides a new idea for the UAV path planning research.