一种无人机局部路径重规划算法研究

Study on a Kind of Local Path Replanning Algorithm for UAVs

提出了一种突发威胁体下无人机局部路径重规划的算法。首先根据不同威胁体的分布情况构造无人机的可飞航路集,用“改进型V orono i图”表示出来,采用D ijkstra算法求解初始粗略最短路径。在无人机飞行过程中,通过基于混合动态贝叶斯网络的切换线性动态系统模型感知环境,应用V iterb i解码算法确定突发威胁体的实时位置及威胁等级,再依据局部路径重规划原则进行寻优,最后应用三次平滑及序列二次规划方法获得实际可飞路径,并用M atlab仿真验证了算法的有效性。

A path planning scheme for unmanned combat air vehicles （UtEAVs） ts devetopeo for achieving the optimal local path replanning under a complicated air-battle environment. Constructing and searching an improved Voronoi diagram based on the locations and grades of the different things, the Dijkstra algorithm is implemented to find an initial thing-avoiding flight path to the target. For matching dynamic battlefield situations and tracking the changing status of suddenly appeared things, a switching linear dynamic system （SLDS） model based on mix-state dynamic Bayesian network （mix-state DBN） is exploited. Viterbi approximation algorithm is then used to estimate the location and the grade of the suddenly appeared thing, Based on the detected states of new thing, Dijkstra algorithm is used again to find the replanned path and further optimized by performing cubic spline and sequential quadratic processing. The Matlab simulation result demonstrates the path planning algorithm is effective.