无人机的侦察航路规划

On Path Planning for More Efficient Reconnaissance of UAV(Unmanned Aerial Vehicle)

针对无人机 ( UAV)侦察任务的两个目标 :( 1 )发现尽可能多的目标 ;( 2 )获得对所有目标尽可能多的有效侦察时间 ,提出了一种优化方法 ,包括航路规划和航路光顺两部分。首先由基于遗传算法 ( GA)的航路规划器根据选定的任务目标制定出优化航路 ,然后由航路光顺器对优化航路进行光顺以形成可供无人机飞行的航路。最后给出了仿真结果 。

We propose to get optimum results of UAV reconnaissance for two cases: (1) the case of finding as many targets as possible, (2) the case of obtaining as much effective reconnaissance time as possible. For example, using our planning method we can find as many as 37 targets in Table 1 but the effective reconnaissance time, expressed in terms of flying distance, is only 1 263km. For example again, using our planning method, we can get as much as 2 498km of reconnaissance flying distance but the reconnaissance information is only about 25 of the 37 targets (Table 2). To get optimum results, the algorithm we proposed includes two parts: the path planner and the path smoother. The planner is used to get the optimum path when the reconnaissance objective is selected and the smoother is then used to smooth optimum path to make it flyable. Section 3 explains in some detail the planner. Essentially, section 3 explains two points: (1) the planner is a class of adaptive search techniques——GA (Genetic Algorithm) based approach——because it is often described as a robust and global search method and because it makes no assumptions about the search space such as gradient and modality; (2) the planner takes into consideration the accommodation of performance constraints (path length, minimum turning radius). Section 4 explains in some detail about the smoother. Simulation results, shown in Figs. 5 and 6 and listed in Tables 1 and 2, show preliminarily that our proposed method of efficient path planning of UAV reconnaissance is feasible.