UAV path planning algorithm based on improved RRT

Abstract

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.

Quadcopter UAV Trajectory Planning Based on Improved Dung Beetle Algorithm

“…Then, a difference strategy, a novel decay function and a population regeneration strategy are introduced to improve the performance of the algorithm [5]. A UAV path planning method based on improved genetic algorithm is proposed in the literature 6, where the parameters of the GA crossover and mutation steps are modified using PSO to drive the trajectory planning to optimality [6]. Article 7 proposes a VPF-RRT* algorithm to plan the planning path; secondly, an anti-environmental perturbation method based on Deep Recurrent Neural Network PI (DRNN-PI) controllers is proposed to enable the USVs to eliminate the environmental perturbations and maintain their trajectories along the planning path [7].…”