Abstract: 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.

Key words: Route planning, Rapidly exploring random tree, Objective heuristic function, UAV dynamic constraints