基于启发式搜索算法的无人机航迹快速规划

基于无人机导航系统的自身特点，无人机在导航过程中会出现无法精确定位的情况，从而产生定位误差。如果不能及时校正随时间累积的定位误差，会使无人机无法到达预定目的地，从而导致飞行任务失败。为避免这种情况的发生，本文研究了考虑定位误差的无人机航迹快速规划问题。以航迹距离最短为目标，考虑定位误差校正约束与航迹约束，建立了混合整数规划模型。根据深度优先搜索算法与回溯算法的特点，设计了启发式深度优先搜索+回溯算法来求解问题，并在此算法基础上加入模拟退火机制对解的质量进行优化。以某飞行区域的数据为例进行仿真实验，结果表明启发式深度优先搜索+回溯算法可以快速有效地求解考虑定位误差的无人机航迹规划问题。

Fast Path Planning of Unmanned Aerial Vehicles Based on Heuristic Search Algorithm

Based on the characteristics of the unmanned aerial vehicle (UAV) navigation system, the UAV cannot locate accurately in the navigation process, which results in positioning errors. If the accumulated positioning error over time cannot be corrected in time, the UAV cannot reach the intended destination, which will lead to the failure of the flight mission. In order to avoid this situation, the problem of fast path planning of UAV considering the positioning error was studied in this paper. A mixed integer programming model was established, which took the shortest path distance as the goal and considered the correction constraint of the positioning error and the path constraint. According to the characteristics of depth-first search (DFS) algorithm and backtracking algorithm, the heuristic DFS+backtracking algorithm was designed to solve the problem, and based on the algorithm, the simulated annealing mechanism was added to optimize the quality of the solution. Taking the data of a certain flight area as an example, the simulation results show that the heuristic DFS+backtracking algorithm can solve the problem of the UAV path planning considering the positioning error quickly and effectively.