无人机集群研究进展综述

doi:10.7527/S1000-6893.2019.23738

Abstract

Abstract: Swarm as a typical collective behavior is omnipresent in animal kingdom, such as fish schooling, bird flocking, and bee swarming. In a colony, large-scale synchronous behavior emerges by virtue of local sensing and very simple communication rules. Inspired by these collective performances, the swarm of unmanned aerial vehicles is proposed as a new combat pattern. These unmanned aerial vehicles are characterized by large quantity, low cost, high speed, well adaptability, and convenient carried/launched mechanism, contributing to the scale advantage of UAVs and the possession of war initiative In recent years, many military powers, such as China, Russia, United States, have made great effort to the continuous development of swarm-related technology of unmanned aerial vehicles. To resolve the swarming problem of unmanned aerial vehicles, this paper introduces the research motivations of UAVs, summarizing the research approaches from modeling, control protocol, and execution platform. Besides, several classical combat modes and involved key technologies are discussed in detail. Above all, the swarm-related technology has bright application potential in the military area, leading to a brand new combat pattern.

Key words: unmanned aerial vehicles, swarming technology, large-scale system, man/unmanned cooperative control, distributed control

CLC Number:

V249.1

JIA Yongnan, TIAN Siying, LI Qing. Recent development of unmanned aerial vehicle swarms[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2020, 41(S1): 723738-723738.

References 86

[1]	宋怡然,申超,李东兵. 美国分布式低成本无人机集群研究进展[J]. 飞航导弹,2016(8):17-22. SONG Y R, SHEN C, LI D B. A review of the research on distributed, low-cost system for unmanned aerial vehicles (UAVs) swarm of the United States[J]. Aerodynamic Missile Journal, 2016(8):17-22(in Chinese).
[2]	陈晶. 解析美海军低成本无人机蜂群技术[J]. 无人机,2016(1):24-26. CHEN J. The US navy's low-cost swarming drone technology[J]. Unmanned Vehicles, 2016(1):24-26(in Chinese).
[3]	REYNOLDS C W. Flocks, herds, and schools:A distributed behavioral model[J]. ACM SIGGRAPH Computer Graphics, 1987, 21(4):25-34.
[4]	VICSEK T, CZIROK A, JACOB E B, et al. Novel type of phase transitions in a system of self-driven particles[J]. Physical Review Letters, 1995, 75(6):1226.
[5]	VICSEK T. A question of scale[J]. Nature, 2001, 411(6836):421.
[6]	JADBABAIE A, LIN J, MORSE A S. Coordination of groups of mobile autonomous agents using nearest neighbor rules[J]. IEEE Transactions on Automatic Control, 2003, 48(6):988-1001.
[7]	GAZI V, PASSINO K M. Stability analysis of swarms[J]. IEEE Transactions on Automatic Control, 2003, 48(4):692-697.
[8]	OLFATI-SABER R. Flocking for multi-agent dynamic systems:Algorithms and theory[J]. IEEE Transactions on Automatic Control, 2006, 51(3):401-420.
[9]	CUCKER F, SMALE S. Emergent behavior in flocks[J]. IEEE Transactions on Automatic Control, 2007, 52(5):852-862.
[10]	吕娜,刘创,陈柯帆,等. 一种面向航空集群的集中控制式网络部署方法[J]. 航空学报, 2018, 39(7):321961. LYU N, LIU C, CHEN K F, et al. A method for centralized control network deployment of aeronautic swarm[J]. Acta Aerodynamic et Astronautica Sinica, 2018, 39(7):321961(in Chinese).
[11]	JING G, ZHENG Y, WANG L. Group flocking of multiple mobile agents[C]//33rd Chinese Control Conference, 2014:1156-1161.
[12]	CHEN Y, CHANG S. An agent-based simulation for multi-UAVs coordinative sensing[J]. International Journal of Intelligent Computing and Cybernetics, 2008, 1(2):269-284.
[13]	CUCKER F, DONG J. Avoiding collisions in flocks[J]. IEEE Transactions on Automatic Control, 2010, 55(5):1238-1243.
[14]	BAYEZIT I, FIDAN B. Distributed cohesive motion control of flight vehicle formations[J]. IEEE Transactions on Industrial Electronics, 2013, 60(12):5763-5772.
[15]	RAHIMI R, ABDOLLAHI F, NAQSHI K. Time-varying formation control of a collaborative heterogeneous multi agent system[J]. Robotics and Autonomous Systems, 2014, 62(12):1799-1805.
[16]	DONG X, YU B, SHI Z, et al. Time-varying formation control for unmanned aerial vehicles:Theories and applications[J]. IEEE Transactions on Control Systems Technology, 2015, 23(1):340-348.
[17]	周绍磊,祁亚辉,张雷,等. 切换拓扑下无人机集群系统时变编队控制[J]. 航空学报, 2017, 38(4):320452. ZHOU S L, QI Y H, ZHANG L, et al. Time-varying formation control of UAV swarm systems with switching topologies[J]. Acta Aeronautica et Astronautica Sinica, 2017, 38(4):320452(in Chinese).
[18]	OYEKAN J. Bio-Inspired vision-based leader-follower formation flying in the presence of delays[J]. Robotics, 2016, 5(3):18.
[19]	KOWNACKI C. Multi-UAV flight using virtual structure combined with behavioral approach[J]. Acta Mechanica et Automatica, 2016,10(2):92-99.
[20]	QIU H, DUAN H. Multiple UAV distributed close formation control based on in-flight leadership hierarchies of pigeon flocks[J]. Aerospace Science and Technology, 2017, 70:471-486.
[21]	ALFEO A L, CIMINO M G C A, DE F N, et al. Design and simulation of the emergent behavior of small drones swarming for distributed target localization[J]. Journal of Computational Science, 2018, 29:19-33.
[22]	JIA Y N, LI Q, ZHANG W C. A distributed cooperative approach for unmanned aerial vehicle flocking[J]. Chaos, 2019, 29(4):043118.
[23]	JIA Y N, YANG Y H, LI Q, et al. Aerial escort task using networked miniature unmanned aerial vehicles[J/OL]. (2019-08-30)[2019-09-11].International Journal of Control, https://www_tandfonline.xilesou.top/doi/abs/10.1080/00207179.2019.1661522.
[24]	BONABEAU E, DORIGO M, THERAULAZ G. Swarm intelligence-from natural to artificial systems[M]. Oxford:Oxford University Press, 1999.
[25]	KUMAR V. The 5S's of aerial robotics:Small, smart, safe, speedy and swarming[C]//CCF-GAIR, 2016.
[26]	HEADQUARTERS. United States air force unmanned aircraft systems flight plan 2016-2036[R]. Washington, D.C.:USAF, 2009.
[27]	CAMBONE S A. Unmanned aircraft systems roadmap 2005-2030[R]. Washington, D.C.:Office of the Secretary of Defense, 2005.
[28]	BALLERINI M, CABIBBO N, CANDELIER R, et al. Interaction ruling animal collective behavior depends on topological rather than metric distance:Evidence from a field study[J]. Proceedings of the National Academy of Sciences of the United States of America, 2008, 105(4):1232-1237.
[29]	COUZIN I D, KRAUSE J, FRANKS N R, et al. Effective leadership and decision-making in animal groups on the move[J]. Nature, 2005, 433(7025):513-516.
[30]	MEHES E, VICSEK T. Collective motion of cells:From experiments to models[J]. Integrative Biology, 2014, 6(9):831-854.
[31]	JIANG L, GIUGGIOLI L, PERNA A, et al. Identifying influential neighbors in animal flocking[J]. PloS Computational Biology, 2017, 13(11):e1005822.
[32]	ALFEO A L, CIMINO M G C A, DE F, et al. Swarm coordination of mini-UAVs for target search using imperfect sensors[J]. Intelligent Decision Technologies, 2018, 12(2):149-162.
[33]	ANDREA C, ALESSIO C, IRENE G, et al. Scale-free correlations in starling flocks[J]. Proceedings of the National Academy of Sciences of the National Academy of Sciences of the United States of America, 2010, 107(26):11865-11870.
[34]	CISZAK M, COMPARINI D, MAZZOLAI B, et al. Swarming behavior in plant roots[J]. PloS One, 2012, 7(1):e29759.
[35]	DEUTSCH A, THERAULAZ G, VICSEK T. Collective motion in biological systems[J]. Interface Focus, 2012, 2(6):689-692.
[36]	LI L, XIAO W B, QIU W, et al. New flocking models apply for UAV formation[J]. Journal of Physics:Conference Series, 2019, 1169:012025.
[37]	BENEDETTI M, DURSO F, FORTINO G, et al. A fault-tolerant self-organizing flocking approach for UAV aerial survey[J]. Journal of Network and Computer Applications, 2017, 96:14-30.
[38]	BAHLOUL N E H, BOUDJIT S, ABDENNEBI M, et al. A flocking-based on demand routing protocol for unmanned aerial vehicles[J]. Journal of Computer Science and Technology, 2018, 33(2):263-276.
[39]	DUAN H B, LI P. Autonomous control for unmanned aerial vehicle swarms based on biological collective behaviors[J]. Science & Technology Review, 2017, 35(7):17-25.
[40]	ZHANG T J. Unmanned aerial vehicle formation inspired by bird flocking and foraging behavior[J]. International Journal of Automation and Computing, 2018, 15(4):402-416.
[41]	QUINTERO S, COLLINS G, HESPANHA J. Flocking with fixed-wing UAVs for distributed sensing:A stochastic optimal control approach[C]//Proceedings of the American Control Conference, 2013:2025-2031.
[42]	ZENKEVICH S L, GALUSTYAN N K. Decentralized control of a quadrocopter swarm[J]. Mechatronics, Automation and Control, 2016, 17(11):774-82.
[43]	QIU H X, DUAN H B. Pigeon interaction mode switch-based UAV distributed flocking control under obstacle environments[J]. ISA Transactions, 2017, 71(1):93-102.
[44]	JIA Y N, LI Q, QIU S Q. Distributed leader-follower flight control for large-scale clusters of small unmanned aerial vehicles[J]. IEEE Access, 2018, 6:32790-32799.
[45]	MAO X, ZHANG H B, WANG Y H. Flocking of quad-rotor UAVs with fuzzy control[J]. ISA Transactions, 2018, 74:185-193.
[46]	ZHAO W, CHU H, ZHANG M, et al. Flocking control of fixed-wing UAVs with cooperative obstacle avoidance capability[J]. IEEE Access, 2019, 7:17798-17808.
[47]	DAI F, CHEN M, WEI X, et al. Swarm intelligence-inspired autonomous flocking control in UAV networks[J]. IEEE Access, 2019, 7:61786-61796.
[48]	SHEN J. Cucker-smale flocking under hierarchical leadership[J]. Society for Industrial and Applied Mathematics, 2006, 68(3):694-719.
[49]	LI B, LI J, HUANG K W. Modeling and flocking consensus analysis for large-scale UAV swarms[J]. Mathematical Problems in Engineering, 2013, 2013:368369.
[50]	VIRÁGH C, VASARHELYI G, TARCAI N, et al. Flocking algorithm for autonomous flying robots[J]. Bioinspiration and Biomimetics, 2014, 9(2):025012.
[51]	HUNG S, GIVIGI S N. A Q-learning approach to flocking with UAVs in a stochastic environment[J]. IEEE Transactions on Cybernetics, 2017, 47(1):186-197.
[52]	VASARHELYI G, VIRAGH C, SOMORJAI G, et al. Optimized flocking of autonomous drones in confined environments[J]. Science Robotics, 2018, 3(20):eaat3536.
[53]	PARANJAPE A A, CHUNG S, KIM K, et al. Robotic herding of a flock of birds using an unmanned aerial vehicle[J]. IEEE Transactions on Robotics, 2018, 34(4):901-915.
[54]	GARCIA G, KESHMIRI S. Biologically inspired trajectory generation for swarming UAVs using topological distances[J]. Aerospace Science and Technology, 2016, 54:312-319.
[55]	KOWNACKI C, OLDZIEJ D. Fixed-wing UAVs flock control through cohesion and repulsion behaviors combined with a leadership[J/OL]. (2016-01-12)[2017-05-15]. International Journal of Advanced Robotic Systems, https://doi.org/10.5772/62249.
[56]	HE L L, BAI P, LIANG X L, et al. Feedback formation control of UAV swarm with multiple implicit leaders[J]. Aerospace Science and Technology, 2018, 72:327-334.
[57]	CHEN M, DAI F, WANG H, et al. DFM:A distributed flocking model for UAV swarm networks[J]. IEEE Access, 2018, 6:69141-69150.
[58]	BEN-ASHER P G Y, FELDMAN S, FELDMAN M. Distributed decision and control for cooperative UAVs using ad hoc communication[J]. IEEE Transactions on Control System Technology, 2008, 16(3):511-516.
[59]	KHARE V R, WANG F Z, WU S, et al. Ad-hoc network of unmanned aerial vehicle swarms for search and destroy tasks[C]//4th International IEEE Conference on Intelligent Systems. Piscataway:IEEE Press, 2008:665-672.
[60]	HAUERT S, LEVEN S, VARGA M, et al. Reynolds flocking in reality with fixed-wing robots:Communication range vs maximum turning rate[C]//IEEE/RSJ International Conference on Intelligent Robot System, 2011:5015-5020.
[61]	KIM S W, SEO S W. Cooperative unmanned autonomous vehicle control for spatially secure group communications[J]. IEEE Journal on Selected Area in Communications, 2012, 30(5):870-882.
[62]	LUO F, JIANG C, DU J, et al. A distributed gateway selection algorithm for UAV networks[J]. IEEE Transactions on Emerging Topics in Computing, 2015, 3(1):22-33.
[63]	BAYEZIT I, FIDAN B. Distributed cohesive motion control of flight vehicle formations[J]. IEEE Transactions on Industrial Electronics, 2013, 60(12):5763-5772.
[64]	CAO W, XU W. A new multi-UAV cooperation method[C]//9th International Symposium on Computational Intelligence and Design, 2016:231-234.
[65]	JIA Y N. Swarming coordination of multiple unmanned aerial vehicles in three-dimensional space[C]//AIAA Modeling and Simulation Technologies Conference. Reston:AIAA, 2016.
[66]	CIARLETTA L, GUENARD A, PRESSE Y, et al. Simulation and platform tools to develop safe flock of UAVs:A cps application-driven research[C]//International Conference on Unmanned Aircraft Systems, 2014:95-102.
[67]	CORNER J J, LAMONT G B. Parallel simulation of UAV swarm scenarios[C]//Proceedings of the Winter Simulation Conference, 2004:363-371.
[68]	MENDEZ L, GIVIGI S N, SCHWARTZ H M, et al. Validation of swarms of robots:Theory and experimental results[C]//7th International Conference on System of Systems Engineering, 2012:332-337.
[69]	SASKA M. Mav-swarms:Unmanned aerial vehicles stabilized along a given path using onboard relative localization[C]//International Conference on Unmanned Aircraft Systems, 2015:894-903.
[70]	GIL A E, PASSINO K M, GANAPATHY S. Cooperative task scheduling for networked uninhabited air vehicles[J]. IEEE Transactions on Aerospace and Electronic Systems, 2008, 4(2):561-581.
[71]	JOELIANTO E, SAGALA A. Swarm tracking control for flocking of a multi-agent system[C]//IEEE Conference on Control, Systems and Industrial Informatics, 2012:75-80.
[72]	VÁSÁRHELYI G, VIRÁGH C, SOMORJAI G, et al. Outdoor flocking and formation flight with autonomous aerial robots[C]//IEEE/RSJ International Conference on Intelligent Robot Systems. Piscataway:IEEE Press, 2014:3866-3873.
[73]	BARABASI A-L, ALBERT R. Emergence of scaling in random networks[J]. Science, 1999, 286(5439):509-512.
[74]	FANG H, WEI Y, CHEN J, et al. Flocking of second-order multiagent systems with connectivity preservation based on algebraic connectivity estimation[J]. IEEE Transactions on Cybernetics, 2017, 47(4):1067-1077.
[75]	SOORKI M N, TAVAZOEI M S. Adaptive robust control of fractional-order swarm systems in the presence of model uncertainties and external disturbances[J]. IET Control Theory & Applications, 2018, 12(7):961-969.
[76]	SAHU B K, SUBUDHI B. Flocking control of multiple AUVs based on fuzzy potential functions[J]. IEEE Transactions on Fuzzy Systems, 2018, 26(5):2539-2551.
[77]	YAZDANI S, HAERI M, SU H. Sampled-data leader-follower algorithm for flocking of multi-agent systems[J]. IET Control Theory and Applications, 2019, 13(5):609-619.
[78]	ZHAN J, LI X. Flocking of multi-agent systems via model predictive control based on position-only measurements[J]. IEEE Transactions on Industrial Informatics, 2013, 9(1):377-385.
[79]	ISKANDARANI M, GIVIGI S N, FUSINA G, et al. Unmanned aerial vehicle formation flying using linear model predictive control[C]//8th Annual IEEE System Conference, 2014:18-23.
[80]	ZHANG H, LIU B, CHENG Z, et al. Model predictive flocking control of the cucker-smale multi-agent model with input constraints[J]. IEEE Transactions on Circuits and Systems I, 2016, 63(8):1265-1275.
[81]	DONG J, QIU L. Flocking of the cucker-smale model on general digraphs[J]. IEEE Transactions on Automatic Control, 2017, 62(10):5234-5239.
[82]	ZHANG H, CHENG Z, CHEN G, et al. Model predictive flocking control for second-order multi-agent systems with input constraints[J]. IEEE Transactions on Circuits and Systems I, 2015, 62(6):1599-1606.
[83]	RAO S, GHOSE D. Sliding mode control-based autopilots for leaderless consensus of unmanned aerial vehicles[J]. IEEE Transactions on Control System Technology, 2014, 22(5):1964-1972.
[84]	JIA Y N, VICSEK T. Modeling hierarchical flocking[J]. New Journal of Physics, 2019, 21:093048.
[85]	JIA Y N, WANG L. Decentralized formation flocking for multiple non-holonomic agents[C]//6th IEEE International Conference on Cybernetics and Intelligent Systems. Piscataway:IEEE Press, 2013:100-105.
[86]	BENNO L, DEMIAN L. The rotating vicsek model:Pattern formation and enhanced flocking in chiral active matter[J]. Physical Review Letters, 2016, 119(5):058002.

Recent development of unmanned aerial vehicle swarms

PDF (PC)

Knowledge

Abstract

Cite this article

share this article

References 86

Related Articles 15

Recommended Articles

Metrics

Comments

[1]	Zhiqiang WEI, Zheming WENG, Yongzhao HUA, Xiwang DONG, Zhang REN. Formation-containment tracking control for heterogeneous unmanned swarm systems with switching topologies [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2023, 44(2): 326504-326504.
[2]	HU Yangxiu, ZHAO Changchun, JIA Chenglong, QIAN Zhouyuan, HU Tao. Synchronous path formation control of UAV swarm based on robot operating system (ROS) [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2022, 43(S1): 726914-726914.
[3]	LIU Fang, HAN Xiao. Adaptive aerial object detection based on multi-scale deep learning [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2022, 43(5): 325270-325270.
[4]	LI Jie, ZHANG Heng, YANG Zhao. Trade-off aerodynamic design of basic wing for demonstrator UAVs with special layout for high-subsonic laminar flow verification [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2022, 43(11): 526786-526786.
[5]	DUAN Dengyan, PEI Jiatao, ZU Rui, LI Jianbo. Power optimization and control of motor variable-pitch propeller propulsion system [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2021, 42(3): 623933-623933.
[6]	HE Wei, FANG Yongchun, LIANG Xiao, ZHANG Peng. Design and implementation of a 2-DOF aerial manipulation system [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2021, 42(2): 324280-324280.
[7]	LIU Deyuan, LIU Hao, Frank L LEWIS. Robust fault-tolerant formation control for tail-sitters [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2021, 42(2): 324296-324296.
[8]	YANG Sen, ZHANG Xianglun. Energy optimized maneuver trajectory generation for unmanned aerial vehicles [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2020, 41(S2): 724288-724288.
[9]	TIAN Bailing, LI Pinpin, LU Hanchen, ZONG Qun. Trajectory and attitude coordinated control of multiple unmanned aerial vehicles (UAVs) in complex environments [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2020, 41(S2): 724245-724245.
[10]	ZHOU Siquan, DONG Xiwang, LI Qingdong, REN Zhang. Time-varying formation control and disturbance rejection for UAV-UGV heterogeneous swarm system [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2020, 41(S1): 723767-723767.
[11]	ZHANG Zhe, WU Jian, DAI Jiyang, YING Jin, HE Cheng. Fast penetration path planning for stealth UAV based on improved A-Star algorithm [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2020, 41(7): 323692-323692.
[12]	LU Yanmei, ZONG Qun, ZHANG Xiuyun, LU Hanchen, ZHANG Ruilong. Formation reconstruction and virtual simulation verification of swarm UAVs [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2020, 41(4): 323580-323580.
[13]	LIU Yuxuan, LIU Hu, TIAN Yongliang, SUN Cong. Distributed control method of multiple UAVs for persistent wildfire surveillance [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2020, 41(2): 323381-323381.
[14]	WANG Enmei, WU Shu'nan, WANG Xiaoming, WU Zhigang. Distributed vibration control for large satellite solar panels [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2018, 39(1): 221479-221479.
[15]	TANG Wei, SONG Bifeng, CAO Yu, YANG Wenqing. Preliminary design method for miniature electric-powered vertical take-off and landing unmanned airial vehicle and effects of special parameters [J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2017, 38(10): 220972-220972.