基于量子遗传算法的多无人机突防路径规划算法OA
Multi-UAV Penetration Path Planning Algorithm Based on Quantum Genetic Algorithm
由于现代军事的特殊要求,无人作战飞机越来越受到世界各国研究人员的关注.它具有生命风险为零、作战能力更强、对恶劣作战环境的适应能力优于有人驾驶飞机等诸多优点.无人机在战场上的广泛应用决定了其在战争中的重要地位.随着军事科学技术的快速发展,军用无人机呈现出集群化、模块化和智能化的特点.然而,在复杂的战场环境下,大量的计算数据与机载计算机有限的计算能力之间存在着冲突.因此,一种稳定高效的路径规划算法至关重要.论文针对多无人机战场环境下突防的场景,用改进的量子遗传算法对无人机进行任务分配及路径规划.实验结果表明,该方法是可行的、快速的、可靠的.
Due to the special requirements of modern military,the UAVs are getting more and more attention from researchers all over the world.It has many advantages,such as zero life risk,stronger combat capability,and better adaptability to harsh com-bat environments than manually controlled aircraft.The wide application of UAV in the battlefield determines its important position in the war.With the rapid development of military science and technology,military UAV presents the characteristics of clustering,modularization and intelligence.However,in the complex battlefield environment,there is a conflict between the large amount of computational data and the limited computing power of the onboard computer.Therefore,a stable and efficient path planning algo-rithm is very important.In this paper,an improved quantum genetic algorithm is used for task assignment and path planning of UAV in the multi-UAV battlefield environment.Experimental results show that this method is feasible,rapid and reliable.
陈旭;李丹
南京航空航天大学计算机科学与技术学院 南京 210000南京航空航天大学计算机科学与技术学院 南京 210000
信息技术与安全科学
多无人机调度无人机突防量子遗传算法
multi-UAV schedulingUAV penetrationquantum genetic algorithm
《计算机与数字工程》 2026 (1)
33-38,47,7
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