基于RRT的无人机动态航路规划算法

UAV Dynamic Route Planning Algorithm Based on RRT

针对传统航路规划算法存在速度慢、航路可飞性差、动态调整能力不足的问题,提出一种基于改进快速扩展随机树(Rapidly Exploring Random Tree,RRT)的无人机动态航路规划算法。首先,引入RRT方法进行全局航路规划,同时为加快算法收敛,在随机树待扩展节点的选取上引入目标启发信息,并在新节点生成和添加过程中融入无人机动力学约束,确保生成的航路具有现实可飞性;其次,为了应对突发威胁情况,提出一种动态扩展随机树的方法来对原有随机树进行剪枝和重构,进而快速避开威胁,生成一条安全航路。实验结果表明,相较于传统RRT算法,改进算法的规划速度提升约20%,节点扩展数减少32%,且规划所得航路符合无人机基本动力学约束条件;当面对突发威胁时,其可以快速进行航路动态调整,实现航路重规划。

Aiming at the problems of slow speed,poor flight ability and insufficient dynamic adjustment ability in traditional route planning algorithms,a dynamic route planning algorithm for UAV based on improved rapidly exploring random tree(RRT)is proposed.Firstly,when the RRT method is introduced for global route planning,in order to accelerate the convergence speed of the algorithm,target heuristic information is introduced in the selection of random tree nodes to be expanded,and UAV dynamic constraints are incorporated in the generation and addition of new nodes to ensure that the generated route has realistic flight abi-lity.Secondly,considering the emergent threat,a method of dynamically expanding random tree is proposed to prune and reconstruct the original random tree,so as to avoid the threat quickly and generate a safe route.Experimental results show that compared with the traditional RRT algorithm,the improved algorithm can improve the planning speed by about 20%and reduce the number of nodes by 32%,and the planned route conforms to the basic dynamics constraints of UAV.In addition,when facing emergent threats,the route can be dynamically adjusted quickly to achieve route re-planning.