摘要
通过预先侦察和经验评估,给出了一种敌情信息未知环境中的无人机路径规划方法。采用Bayes方法求取了给定规划区域内威胁存在的概率,构建了威胁概率分布图,并将其转化成权重为威胁概率的带权图,利用Bellman-Ford算法搜索该带权图,求取了一条从出发点到目标点的无人机最小威胁路径,根据无人机气动性能约束,对最小威胁路径进行了修正和优化,得到一条可飞的最优路径,最后给出了仿真结果,验证了方法的有效性。
An unmanned aerial vehicle （UAV） path＇ planning method in uncertain and adversarial environment is proposed based on the prior surveillance and experiential evaluation. Bayes rule is used to get the probability of threats in the given planning area, the probability map is constructed and then used to generate a weighted diagram, and the link weight of the diagram is the threat probability of related cell in the probability map, Bellman-Ford algorithm is used to search a minimum risk path of UAV from the origin to the target in the weighted diagram. Based on the maneuverability constraints of UAV, the minimum risk path is optimized to an optimal path. Through the simulation results of the algorithm, the validity of this method is proved successfully.
出处
《弹箭与制导学报》
CSCD
北大核心
2007年第5期249-251,共3页
Journal of Projectiles,Rockets,Missiles and Guidance
