面向多无人机协同对地攻击的双层任务规划方法

doi:10.12305/j.issn.1001-506X.2022.09.19

Abstract

Abstract:

The unmanned aerial vehicles (UAVs) mission planning consists of task allocation, mission sequence assignment and trajectory planning. These optimization problems are interacted. To achieve the global optimal solution of the UAVs mission planning, these three optimization problems should be fully considered and organized. In this paper, considering the requirements and interactions among the three optimization problems, a double-level planning framework is firstly introduced, and then the whole mission planning problem is decomposed into two parts: the high level task allocation and the low level sequence optimization. The optimization models and methods for each level are subsequently developed and detailed. In the process of task allocation, a simulated-annealing-shooting (SAS) is proposed for overcoming the local-optimal-trap, and the configuration principle of the algorithm parameters are discussed. Finally, the simulation results demonstrate the effectiveness of the proposed planning framework and the SAS algorithm.

Key words: unmanned aerial vehicle (UAV), mission planning, simulated-annealing algorithm, planning framework, optimization algorithm

CLC Number:

TP391

Jing YU, Enmi YONG, Hanyang CHEN, Dong HAO, Xiancai ZHANG. Bi-level mission planning method for multi-cooperative UAV air-to-ground attack[J]. Systems Engineering and Electronics, 2022, 44(9): 2849-2857.

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References 19

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UAV_i	tar₁	tar₂	tar₃	tar₄	tar₅	tar₆	tar₇	tar₈	tar₉	tar₁₀
UAV₁	0.864	0.811	0.846	0.945	0.805	0.762	0.768	0.829	0.777	0.767
UAV₂	0.789	0.888	0.831	0.938	0.982	0.790	0.751	0.755	0.823	0.735
UAV₃	0.923	0.934	0.834	0.893	0.963	0.841	0.768	0.971	0.878	0.789
UAV₄	0.757	0.724	0.792	0.814	0.865	0.769	0.831	0.994	0.779	0.796
UAV₅	0.906	0.979	0.853	0.943	0.887	0.953	0.793	0.832	0.881	0.827
UAV₆	0.755	0.933	0.853	0.860	0.876	0.758	0.977	0.733	0.913	0.852

UAV_i	tar₁	tar₂	tar₃	tar₄	tar₅	tar₆	tar₇	tar₈	tar₉	tar₁₀
UAV₁	0.732	0.725	0.755	0.865	0.821	0.825	0.801	0.773	0.873	0.713
UAV₂	0.989	0.820	0.779	0.743	0.723	0.715	0.970	0.821	0.718	0.751
UAV₃	0.701	0.778	0.744	0.956	0.772	0.971	0.811	0.729	0.770	0.895
UAV₄	0.932	0.940	0.741	0.887	0.737	0.983	0.733	0.740	0.806	0.920
UAV₅	0.945	0.829	0.961	0.805	0.755	0.847	0.934	0.983	0.946	0.894
UAV₆	0.961	0.973	0.874	0.854	0.772	0.847	0.817	0.987	0.705	0.835

参数	数值
起始温度	250
终止温度	10
降温系数	0.99
常温迭代次数	250
邻域搜索位置数目	1, 3, 5, 10
撒点算子规模	5, 10, 50, 100

运行	1	2	3	4	5	均值	方差
1	4.025 0	4.025 0	4.003 5	3.987 0	3.963 0	4.000 7	0.000 699
3	4.003 5	3.981 5	4.025 0	3.997 5	4.025 0	4.006 5	0.000 350
5	4.003 5	3.997 5	3.977 5	3.973 5	3.973 5	3.985 1	0.000 205
10	3.960 0	3.997 5	3.988 5	3.957 5	3.979 0	3.976 5	0.000 306

运行	1	2	3	4	5	均值	方差
5	3.940 0	3.952 0	3.948 0	3.956 0	3.959 5	3.951 1	0.000 057
10	3.973 5	3.961 5	3.968 5	3.988 5	3.987 0	3.975 8	0.000 137
50	4.003 5	3.981 5	4.025 0	3.997 5	4.025 0	4.006 5	0.000 350
100	3.979 0	3.997 5	4.003 5	4.025 0	4.025 0	4.006 0	0.000 382

Bi-level mission planning method for multi-cooperative UAV air-to-ground attack

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UAV_i	任务集合
UAV₁	4
UAV₂	5
UAV₃	6
UAV₄	10
UAV₅	1, 3, 8, 9
UAV₆	2, 7

坐标	tar₁	tar₂	tar₃	tar₄	tar₅	tar₆	tar₇	tar₈	tar₉	tar₁₀
X/km	5	20	30	40	50	55	10	50	40	20
Y/km	50	30	40	10	50	20	55	10	55	56

威胁类型	编号	坐标(x, y)/km	威胁半径/km
雷达探测威胁	1	(26, 55)	5
雷达探测威胁	2	(35, 26)	4
导弹威胁	3	(10, 30)	6
导弹威胁	4	(14, 46)	4
气候威胁	5	(24, 10)	6
地形威胁	6	(52, 40)	2

UAV_i	任务集合	任务序列枚举
UAV₁	4	4(一种组合)
UAV₂	5	5(一种组合)
UAV₃	6	6(一种组合)
UAV₄	10	10(一种组合)
UAV₅	1, 3, 8, 9	24种组合
UAV₆	2, 7	(2, 7)和(7, 2)两种组合

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