Aiming at the problems of traditional Rapidly Exploring Random Tree (RRT) algorithm in route planning, such as slow speed, poor route quality and low flightability, a route planning algorithm based on integrated improvement of RRT was proposed. Firstly, in the selection of nodes to be expanded, the minimum sum of the distance between nodes and the target and the random sampling point is taken as the selection basis instead of the original method of determining nodes only according to random sampling points, so as to increase the probability of nodes near the target in the random tree being selected as nodes to be expanded. Secondly, in the process of node expansion, the reachable region of the next waypoint was determined according to the UAV dynamic constraints, and then multiple alternative nodes were randomly generated in this region. Then the route cost function is designed and the comprehensive generation value of the route formed by the alternative nodes is taken as the judgment criterion for node addition. Finally, B-spline curve smoothing is carried out to further improve the route quality. The simulation results show that the improved algorithm has obvious advantages in improving the planning speed and air route quality, and the obtained air route satisfies the UAV dynamic constraints and has high flightability.
An improved algorithm based on fast extended random tree (RRT) was proposed to solve the 3d route planning problem of uav in complex environment. Firstly, the planning space modeling is carried out according to the threat factors of flight route. Secondly, in view of the large randomness of THE RRT algorithm, the heuristic distance function is introduced as the basis for the selection of nodes to be expanded, so as to increase the probability of nodes near the target being selected as nodes to be expanded, and improve the way of generating new nodes in the random tree to accelerate the convergence speed of the algorithm. Then, UAV dynamics constraints were incorporated into the new node to meet the flight path requirements. Finally, b-spline curve was used to optimize the smoothness of the initial route curvature discontinuity problem. Simulation results show that the improved algorithm has certain advantages in planning speed and route length, and can effectively solve the problem of UAV 3D route planning.
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