A hybrid evolution Jaya algorithm for meteorological drone trajectory planning

Abstract

Aiming at the problems of unreasonable search range and low optimization performance in meteorological drone trajectory planning under complex obstacle threat environments, as well as the shortcomings of sometimes low and unstable optimization accuracy of the basic Jaya algorithm and easy to fall into local optima, a meteorological drone trajectory planning method based on multi-strategy improvement Jaya algorithm optimization is proposed. In order to meet the practical applications, the performance index trajectory planning model based on the weight coefficient method with the spherical coordinate system is established using the shortest trajectory, the minimum threat, the flight altitude, and the flight angle as the performance indexes, as well as the obstacles as the constraints. The simulation results of the improved algorithm for its solution are given, and the performance is compared with other heuristic algorithms. The results show that the planned path can be safer and more effective in avoiding hazardous sources by comprehensively considering the performance of the meteorological drone. Compared with other algorithms, the improved algorithm performs well in terms of searching accuracy and stability and generates the higher-quality trajectory.