Research on unmanned swarm scheduling strategies for mountain obstacle-breaching missions

doi:10.23919/JSEE.2026.000012

Journal of Systems Engineering and Electronics ›› 2026, Vol. 37 ›› Issue (1): 26-35.doi: 10.23919/JSEE.2026.000012

• PERCEPTION, CONTROL, AND DECISION-MAKING OF EMBODIED INTELLIGENT SYSTEMS • Previous Articles Next Articles

Research on unmanned swarm scheduling strategies for mountain obstacle-breaching missions

Kaisheng WANG(), Yanyan HUANG(), Jinxi TAN(), Wenjie ZHAI()

School of Automation, Nanjing University of Science and Technology, Nanjing 210094, China

Received:2025-11-10 Online:2026-02-18 Published:2026-03-09
Contact: Yanyan HUANG E-mail:cauchy1220@njust.edu.cn;huangyy@njust.edu.cn;tanjinxi@njust.edu.cn;15633691362@163.com
About author:
WANG Kaisheng was born in 1999. He received his B.S. degree in electrical engineering from Nanjing University of Science and Technology (NJUST), Nanjing, China, in 2021. He is pursuing his Ph.D. degree at NJUST. His research interests are system modeling and simulation, mission planning, and combat effectiveness evaluation. E-mail: cauchy1220@njust.edu.cn

HUANG Yanyan was born in 1973. He received his B.S. degree from Wuhan University of Science and Technology, Wuhan, China, in 1998, and Ph.D. degree from National University of Defense Technology, Changsha, China, in 2006. He is a professor at Nanjing University of Science and Technology. His research interests are system engineering, effectiveness evaluation, command and control, planning and auxiliary decision-making. E-mail: huangyy@njust.edu.cn

TAN Jinxi was born in 2003. She is pursuing her B.S. degree in smart grid information engineering at Nanjing University of Science and Technology. Her research interests are system engineering and intelligent task planning. E-mail: tanjinxi@njust.edu.cn

ZHAI Wenjie was born in 2000. He received his B.S. degree in electrical engineering from Hebei University of Science and Technology, Hebei, China, in 2022. He is pursuing his Ph.D. degree at Nanjing University of Science and Technology. His research interests are complex network modeling, system planning and simulation. E-mail: 15633691362@163.com
Supported by:
This work was supported by the National Natural Science Foundation of China (61374186).

Abstract

Abstract:

In response to the challenges faced by unmanned swarms in mountain obstacle-breaching missions within complex terrains, such as poor task-resource coupling, lengthy solution generation times, and poor inter-platform collaboration, an unmanned swarm scheduling strategy tailored is proposed for mountain obstacle-breaching missions. Initially, by formalizing the descriptions of obstacle breaching operations, the swarm, and obstacle targets, an optimization model is constructed with the objectives of expected global benefit, timeliness, and task completion degree. A meta-task decomposition and reassembly strategy is then introduced to more precisely match the capabilities of unmanned platforms with task requirements. Additionally, a meta-task decomposition optimization model and a meta-task allocation operator are incorporated to achieve efficient allocation of swarm resources and collaborative scheduling. Simulation results demonstrate that the model can accurately generate reasonable and feasible obstacle breaching execution plans for unmanned swarms based on specific task requirements and environmental conditions. Moreover, compared to conventional strategies, the proposed strategy enhances task completion degree and expected returns while reducing the execution time of the plans.

Key words: mountain obstacle breaching, unmanned swarm, task scheduling, meta-task

Kaisheng WANG, Yanyan HUANG, Jinxi TAN, Wenjie ZHAI. Research on unmanned swarm scheduling strategies for mountain obstacle-breaching missions[J]. Journal of Systems Engineering and Electronics, 2026, 37(1): 26-35.

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Parameter	Value
Number of reconnaissance UAVs	3
Number of UGVs	3
Number of integrated UAVs	4
Maneuvering speed of UAVs/(km/h)	120
Maneuvering speed of UGVs/(km/h)	80
Reconnaissance radius of UAVs/km	10
Obstacle-breaching radius of UAVs/km	10
Obstacle-breaching radius of UGVs/km	10
Sensing payload of reconnaissance UAVs	15
Munition payload of UGVs/pieces	6
Sensing payload of integrated UAVs/times	15
Munition payload of integrated UAVs/pieces	6
Time consumed for reconnaissance/min	5
Time consumed for destruction/min	5
Time consumed for assessment/min	5

ID	Position	Q_r	Q_d	Q_e	v	o
1	(57,69)	3	4	3	15	0.93
2	(38,59)	3	2	4	11	0.53
3	(59,58)	1	2	1	15	0.67
4	(72,61)	1	3	1	11	0.92
5	(64,63)	3	2	2	14	0.14
6	(60,57)	3	1	2	10	0.14
7	(80,76)	2	3	3	11	0.35
8	(61,50)	4	2	1	12	0.68
9	(41,50)	3	1	2	10	0.44
10	(47,52)	4	4	4	13	0.07
11	(99,61)	2	1	1	10	0.11
12	(56,48)	2	2	4	14	0.35
13	(85,60)	4	2	4	11	0.8
14	(69,64)	2	4	4	11	0.48
15	(55,40)	3	2	1	15	0.54
16	(53,72)	4	3	1	14	0.48
17	(57,53)	2	4	4	12	0.95
18	(71,40)	4	1	3	12	0.02
19	(70,54)	2	4	4	15	0.7
20	(45,60)	3	2	2	12	0.06

T	R₁	R₂	R₃	R₄	R₅	R₆	R₇	R₈	R₉	R₁₀	R₁₁
T₁	0	0	0	0	0	0	0	3	2	1	4
T₂	2	0	0	3	0	2	0	0	0	0	2
T₃	3	0	1	0	0	0	0	0	0	0	0
T₄	4	1	0	0	0	0	0	0	0	0	0
T₅	2	0	3	0	1	1	0	0	0	0	0
T₆	0	6	0	0	0	0	0	0	0	0	0
T₇	0	1	4	0	3	0	0	0	0	0	0
T₈	7	0	0	0	0	0	0	0	0	0	0
T₉	2	4	0	0	0	0	0	0	0	0	0
T₁₀	7	0	0	5	0	0	0	0	0	0	0
T₁₁	3	1	0	0	0	0	0	0	0	0	0
T₁₂	8	0	0	0	0	0	0	0	0	0	0
T₁₃	1	5	1	3	0	0	0	0	0	0	0
T₁₄	0	0	0	0	10	0	0	0	0	0	0
T₁₅	0	1	0	2	3	0	0	0	0	0	0
T₁₆	0	8	0	0	0	0	0	0	0	0	0
T₁₇	0	0	0	0	0	1	4	0	2	1	2
T₁₈	0	8	0	0	0	0	0	0	0	0	0
T₁₉	10	0	0	0	0	0	0	0	0	0	0
T₂₀	7	0	0	0	0	0	0	0	0	0	0

m	T_S	I_T	Q_t	Q_q	m	T_S	I_T	Q_t	Q_q
1	23.4	2	1	3	7	74.6	12	2	2
	54.1	13	1	4		84.7	19	2	4
	82.5	6	1	3		89.7	19	3	4
	102	6	3	2		113	5	3	2
	121	13	3	3		62.9	17	1	2
2	27.6	3	1	1	8	26.3	8	1	4
	45.9	11	1	2		91.3	8	2	2
	64	7	1	2		118	8	3	1
	88.6	15	1	1		101	5	2	2
	99	18	1	4		50.2	15	1	2
	131	11	3	1		132	13	3	1
	147	18	3	3		107	14	2	2
	170	3	3	1		142	7	3	3
3	31.5	4	1	1		172	15	3	1
	43.3	12	1	2		69.9	1	1	3
	79.6	12	3	4	9	21.6	9	1	3
	106	4	3	1		40.1	20	1	3
	60.2	14	1	2		55.1	20	2	2
	113	14	3	4		106	20	3	2
4	32.6	3	2	2		63.7	9	2	1
	74.1	13	2	2		120	9	3	2
	84.6	14	2	2		70.8	10	2	1
5	36.5	4	2	3		93.6	15	2	2
5	74	7	2	3		142	2	3	4
6	55.9	11	2	1	10	23.4	10	1	4
	97.5	6	2	1		77.3	10	2	3
	119	18	2	1		50.3	16	1	4
	137	2	2	2		89.2	16	2	3
	148	17	2	1		94.2	16	3	1
7	29.9	5	1	3		106	10	3	4
7	48.5	19	1	2	−	−	−	−	−

Strategy	F_A	E_A	T_A/min
MTDARS	0.9	144.5	176.7
CS	0.85	117.9	191.8

Research on unmanned swarm scheduling strategies for mountain obstacle-breaching missions

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References 30

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I_T	M_T	M_C	M_R	I_T	M_T	M_C	M_R
1	10	3	7	11	4	4	0
2	9	9	0	12	8	8	0
3	4	4	0	13	10	10	0
4	5	5	0	14	10	10	0
5	7	7	0	15	6	6	0
6	6	6	0	16	8	8	0
7	8	8	0	17	10	3	7
8	7	7	0	18	8	8	0
9	6	6	0	19	10	10	0
10	12	12	0	20	7	7	0

I_T	M_T	M_C	M_R	I_T	M_T	M_C	M_R
1	10	10	0	11	4	4	0
2	9	9	0	12	8	8	0
3	4	4	0	13	10	10	0
4	5	5	0	14	10	10	0
5	7	7	0	15	6	6	0
6	6	6	0	16	8	8	0
7	8	8	0	17	10	10	0
8	7	7	0	18	8	4	4
9	6	6	0	19	10	2	8
10	12	12	0	20	7	3	4

Experiment	Strategy	F_A	E_A	T_A/min
1	MTDARS	0.9	139.1	192.77
1	CS	0.85	119.68	205.8
2	MTDARS	0.9	142.58	187.62
2	CS	0.85	117.29	189.16
3	MTDARS	0.9	144.68	178.77
3	CS	0.85	117.89	180.71
4	MTDARS	0.9	144.25	176.03
4	CS	0.85	120.28	181.22
5	MTDARS	0.7	122.39	145.03
5	CS	0.3	95.695	153.16
6	MTDARS	1	145.09	191.36
6	CS	1	132.44	209.51

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I_T	M_T	M_C	M_R	I_T	M_T	M_C	M_R
1	10	3	7	11	4	4	0
2	9	9	0	12	8	8	0
3	4	4	0	13	10	10	0
4	5	5	0	14	10	10	0
5	7	7	0	15	6	6	0
6	6	6	0	16	8	8	0
7	8	8	0	17	10	3	7
8	7	7	0	18	8	8	0
9	6	6	0	19	10	10	0
10	12	12	0	20	7	7	0

I_T	M_T	M_C	M_R	I_T	M_T	M_C	M_R
1	10	10	0	11	4	4	0
2	9	9	0	12	8	8	0
3	4	4	0	13	10	10	0
4	5	5	0	14	10	10	0
5	7	7	0	15	6	6	0
6	6	6	0	16	8	8	0
7	8	8	0	17	10	10	0
8	7	7	0	18	8	4	4
9	6	6	0	19	10	2	8
10	12	12	0	20	7	3	4

I_T	M_T	M_C	M_R	I_T	M_T	M_C	M_R
1	10	3	7	11	4	4	0
2	9	9	0	12	8	8	0
3	4	4	0	13	10	10	0
4	5	5	0	14	10	10	0
5	7	7	0	15	6	6	0
6	6	6	0	16	8	8	0
7	8	8	0	17	10	3	7
8	7	7	0	18	8	8	0
9	6	6	0	19	10	10	0
10	12	12	0	20	7	7	0

I_T	M_T	M_C	M_R	I_T	M_T	M_C	M_R
1	10	10	0	11	4	4	0
2	9	9	0	12	8	8	0
3	4	4	0	13	10	10	0
4	5	5	0	14	10	10	0
5	7	7	0	15	6	6	0
6	6	6	0	16	8	8	0
7	8	8	0	17	10	10	0
8	7	7	0	18	8	4	4
9	6	6	0	19	10	2	8
10	12	12	0	20	7	3	4