基于分组教与学的无人战斗机自适应路径规划OA北大核心CSTPCD

Aiming at the path planning problem of Unmanned Combat Air Vehicle(UCAV)in the battlefield where UCAV is located in a threat area,a UCAV adaptive path planning method based on the algorithm of modified teaching-learning-based optimization is proposed.By analyzing the evaluation index of UCAV path,an adaptive UCAV path evaluation model is proposed,and the mission path with short distance and small threat is planned according to the combat environment.Then,aiming at the problems of low precision and long time consuming in the optimization of teaching and learning algorithm,the algorithm of modified teaching-learning-based optimization is proposed,and dynamic grouping and Gaussian distribution perturbation strategy are introduced to improve the optimization performance of the algorithm.The simulation results show that the optimal path is shorter and safer.