论文部分内容阅读
现有航迹规划方法无法保证规划最优路径的同时满足实时性要求,因此文中提出基于文化算法的无人飞行器航迹规划算法.利用文化算法的特性,将在线航迹规划方法与离线航迹规划方法相结合,融入文化算法种群空间中.知识提取,将初始航迹提取为形势知识,将航迹中特征节点可变化范围提取为规范知识,使用知识限定规划空间,缩短规划时间.通过知识结合不同规划方法,弥补现有方法的缺点.实验验证文中算法在复杂动态环境下能有效寻找目标点,相比其它在线航迹规划方法,规划速度更快,规划航迹更短,有效减少飞行器执行任务的时间.
The existing trajectory planning methods can not guarantee the optimal path planning while meeting the real-time requirements, so the paper proposes a trajectory planning algorithm based on cultural algorithms for UAVs.Using the characteristics of cultural algorithms, the online trajectory planning method and offline trajectory Planning method to integrate into the cultural algorithm population space.According to the knowledge extraction, the initial track is extracted as the situation knowledge, the variable range of the characteristic nodes in the track is extracted as the normative knowledge, and the knowledge is used to limit the planning space and shorten the planning time.Through the knowledge Combined with different planning methods to make up for the shortcomings of the existing methods.Experimental verification algorithm in the paper under complex dynamic environment can effectively find the target point, compared to other online flight path planning methods, planning faster, shorter planning trajectory, and effectively reduce the aircraft Time to perform the task.