未知环境中的无人机航迹搜索策略

为了让无人机具有在未知环境中完成任务的能力,无人机必须根据实际的环境变化进行实时的快速的航迹规划。针对这个问题,通过将滚动时域优化思想与A*搜索算法相结合,提出了一种实时局部优化航迹搜索(LORS)策略。该算法借鉴A*算法的基本思想,并且考虑未知环境的特点和无人机自身的限制,采取滚动时域优化的思想对航迹进行在线实时规划,在生成可飞航迹的同时大大地减少了计算量。通过仿真结果表明,该算法可以针对未知环境中的固定和低速运动威胁,实时地生成满意的航迹。

Route search strategy for unmanned air vehicle in unknown environment

For implementing missions in unknown environment,the UAVs must be capable of making route plan in real-time according to practical environmental changes.To solve the problem,we present a kind of realtime Local Optimization Route Search(LORS) strategy,which integrates the basic thought of rolling time-domain optimization with A* algorithm.Using the basic thought of the A* algorithm,and considering the characteristics of the unknown environment and limits of UAV itself,the algorithm implement on-line route planning with the help of rolling time-domain optimization.It can not only generate a flyable route,but also reduce the calculation cost.According to the result of simulation,the algorithm can generate satisfied paths in the unknown the environment where static and slowly-moving threats exist.