Science and Technology Foresight ›› 2022, Vol. 1 ›› Issue (4): 40-54.DOI: 10.3981/j.issn.2097-0781.2022.04.003
• Review and Commentary • Previous Articles Next Articles
MIAO Haochun(), LIU Zhong, WANG Gen
Received:
2022-10-24
Revised:
2022-10-30
Online:
2022-12-20
Published:
2023-01-17
作者简介:
苗昊春,研究员,西安现代控制技术研究所技术部主任。中国兵器青年科技带头人。主要研究方向为飞行器制导控制,主持和参与了多项重点国防科研项目。入选第三届中国科协青年人才托举工程。获2019年度陕西省青年科技新星,第15届陕西省国防科技工业十大杰出青年等荣誉。出版专著1部,发表论文10余篇,获授权国防专利30余项。电子信箱:357285772@qq.com。
MIAO Haochun, LIU Zhong, WANG Gen. Research Status and Prospects of Cooperative Guidance and Control Technology[J]. Science and Technology Foresight, 2022, 1(4): 40-54.
苗昊春, 刘重, 王根. 协同制导控制技术发展现状及展望[J]. 前瞻科技, 2022, 1(4): 40-54.
Add to citation manager EndNote|Ris|BibTeX
URL: http://www.qianzhankeji.cn/EN/10.3981/j.issn.2097-0781.2022.04.003
[1] |
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.
DOI URL |
[2] |
Yong E. Autonomous drones flock like birds[J]. Nature, 2014, doi: 10.1038/nature.2014.14776.
DOI |
[3] | Office of the Secretary of Defense, United States Department of Defense Office of the Secretary of Defense. Unmanned aircraft systems roadmap:2005-2030[M]. Washington, D. C.: Defense Office of the Secretary of Defense, 2005. |
[4] | 宗群, 王丹丹, 邵士凯, 等. 多无人机协同编队飞行控制研究现状及发展[J]. 哈尔滨工业大学学报, 2017, 49(3): 1-14. |
[5] | Anderson B D O, Fidan B, Yu C B, et al. UAV formation control: Theory and application[M]// Lecture Notes in Control and Information Sciences. London: Springer London, 2007: 15-33. |
[6] |
Kamel M A, Yu X, Zhang Y M. Formation control and coordination of multiple unmanned ground vehicles in normal and faulty situations: A review[J]. Annual Reviews in Control, 2020, 49: 128-144.
DOI URL |
[7] |
Hadi B, Khosravi A, Sarhadi P. A review of the path planning and formation control for multiple autonomous underwater vehicles[J]. Journal of Intelligent & Robotic Systems, 2021, doi: 10.1007/s10846-021-01330-4.
DOI |
[8] | 刘楚豪. 基于集中式控制的多个无人飞行器编队[J]. 华中科技大学学报(自然科学版), 2015, 43(增刊1): 481-485. |
[9] |
Kada B, Khalid M, Shaikh M S. Distributed cooperative control of autonomous multi-agent UAV systems using smooth control[J]. Journal of Systems Engineering and Electronics, 2020, 31(6): 1297-1307.
DOI URL |
[10] |
Dutta R, Sun L, Pack D. A decentralized formation and network connectivity tracking controller for multiple unmanned systems[J]. IEEE Transactions on Control Systems Technology, 2018, 26(6): 2206-2213.
DOI URL |
[11] | Ren W, Beard R W. Distributed consensus in multi-vehicle cooperative control[M]. London: Springer London, 2008. |
[12] | 段海滨. 基于群体智能的无人机集群自主控制[M]. 北京: 科学出版社, 2019. |
[13] |
Gazi V. Swarm aggregations using artificial potentials and sliding-mode control[J]. IEEE Transactions on Robotics, 2005, 21(6): 1208-1214.
DOI URL |
[14] |
Balch T, Arkin R C. Behavior-based formation control for multirobot teams[J]. IEEE Transactions on Robotics and Automation, 1998, 14(6): 926-939.
DOI URL |
[15] | Saber R O, Murray R M. Consensus protocols for networks of dynamic agents[C]// Proceedings of the 2003 American Control Conference. Piscataway: IEEE Press, 2003: 951-956. |
[16] |
Olfati-Saber R, Murray R M. Consensus problems in networks of agents with switching topology and time-delays[J]. IEEE Transactions on Automatic Control, 2004, 49(9): 1520-1533.
DOI URL |
[17] |
Ren W, Beard R W. Consensus seeking in multiagent systems under dynamically changing interaction topologies[J]. IEEE Transactions on Automatic Control, 2005, 50(5): 655-661.
DOI URL |
[18] |
Ren W, Atkins E. Distributed multi-vehicle coordinated controlvia local information exchange[J]. International Journal of Robust and Nonlinear Control, 2007, 17(10-11): 1002-1033.
DOI URL |
[19] |
Yu W W, Chen G R, Cao M, et al. Second-order consensus for multiagent systems with directed topologies and nonlinear dynamics[J]. IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), 2010, 40(3): 881-891.
DOI URL |
[20] |
Kolaric P, Chen C, Dalal A, et al. Consensus controller for multi-UAV navigation[J]. Control Theory and Technology, 2018, 16(2): 110-121.
DOI URL |
[21] |
Baldivieso-Monasterios P R, Trodden P A. Coalitional predictive control: Consensus-based coalition forming with robust regulation[J]. Automatica, 2021, 125: 109380.
DOI URL |
[22] |
Zhao Y, Liu Y, Wen G, et al. Edge-based finite-time protocol analysis with final consensus value and settling time estimations[J]. IEEE Transactions on Cybernetics, 2020, 50(4): 1450-1459.
DOI PMID |
[23] |
Vicsek T, Czirók A, Ben-Jacob E, et al. Novel type of phase transition in a system of self-driven particles[J]. Physical Review Letters, 1995, 75(6): 1226-1229.
PMID |
[24] |
Lu X B, Zhang C, Qin B Z. An improved Vicsek model of swarm based on remote neighbors strategy[J]. Physica A: Statistical Mechanics and its Applications, 2022, 587: 126553.
DOI URL |
[25] | 邱华鑫, 段海滨, 范彦铭. 基于鸽群行为机制的多无人机自主编队[J]. 控制理论与应用, 2015, 32(10): 1298-1304. |
[26] | 吕永申, 刘力嘉, 杨雪榕, 等. 人工势场与虚拟结构相结合的无人机集群编队控制[J]. 飞行力学, 2019, 37(3): 43-47. |
[27] |
Liu Y, Huang P F, Zhang F, et al. Distributed formation control using artificial potentials and neural network for constrained multiagent systems[J]. IEEE Transactions on Control Systems Technology, 2020, 28(2): 697-704.
DOI URL |
[28] |
Hwang J, Lee J, Park C. Collision avoidance control for formation flying of multiple spacecraft using artificial potential field[J]. Advances in Space Research, 2022, 69(5): 2197-2209.
DOI URL |
[29] |
Wang N, Dai J Y, Ying J. UAV formation obstacle avoidance control algorithm based on improved artificial potential field and consensus[J]. International Journal of Aeronautical and Space Sciences, 2021, 22(6): 1413-1427.
DOI URL |
[30] |
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.
DOI URL |
[31] |
Arrichiello F, Chiaverini S, Indiveri G, et al. The null-space-based behavioral control for mobile robots with velocity actuator saturations[J]. The International Journal of Robotics Research, 2010, 29(10): 1317-1337.
DOI URL |
[32] | Ahmad S, Feng Z, Hu G Q. Multi-robot formation control using distributed null space behavioral approach[C]// 2014 IEEE International Conference on Robotics and Automation (ICRA). Piscataway: IEEE Press, 2014: 3607-3611. |
[33] |
Li B, Zhang J W, Dai L, et al. A hybrid offline optimization method for reconfiguration of multi-UAV forma-tions[J]. IEEE Transactions on Aerospace and Electronic Systems, 2021, 57(1): 506-520.
DOI URL |
[34] |
Fukushima H, Kon K, Matsuno F. Model predictive formation control using branch-and-bound compatible with collision avoidance problems[J]. IEEE Transactions on Robotics, 2013, 29(5): 1308-1317.
DOI URL |
[35] | 王勋. 基于拟态物理学的无人机编队控制与重构方法研究[D]. 长沙: 国防科技大学, 2016. |
[36] | Giulietti F, Pollini L, Innocenti M. Autonomous formation flight[J]. IEEE Control Systems Magazine, 2000, 20(6): 34-44. |
[37] |
Fu X W, Pan J, Wang H X, et al. A formation maintenance and reconstruction method of UAV swarm based on distributed control[J]. Aerospace Science and Technology, 2020, doi: 10.1016/j.ast.2020.105981.
DOI |
[38] | 王寅, 王道波, 王建宏. 基于凸优化理论的无人机编队自主重构算法研究[J]. 中国科学(技术科学), 2017, 47(3): 249-258. |
[39] |
Jin P F, Yu J Q, Jia Z Y, et al. Optimal formation control for quadrotors with collision avoidance based on dynamic constraints[J]. Journal of Physics: Conference Series, 2019, doi: 10.1088/1742-6596/1215/1/012018.
DOI |
[40] | Xu G Y, Zhao D, Wang J C, et al. Distributed control of UAV formation reconfiguration in terms of dynamic reference point[J]. International Journal of Control and Automation, 2017, 10(1): 155-166. |
[41] | Zhu T, Ling H F, He W X. A cooperative control approach of UAV autonomous formation and reconfiguration[C]// 2018 Chinese Control and Decision Conference (CCDC). Piscataway: IEEE Press, 2018: 2415-2420. |
[42] |
Kim D Y, Woo B, Park S Y, et al. Hybrid optimization for multiple-impulse reconfiguration trajectories of satellite formation flying[J]. Advances in Space Research, 2009, 44(11): 1257-1269.
DOI URL |
[43] |
Wu Y, Gou J Z, Hu X T, et al. A new consensus theory-based method for formation control and obstacle avoidance of UAVs[J]. Aerospace Science and Technology, 2020, doi: 10.1016/j.ast.2020.106332.
DOI |
[44] | Chevet T, Vlad C, Maniu C S, et al. Decentralized MPC for UAVs formation deployment and reconfiguration with multiple outgoing agents[J]. Journal of Intelligent & Robotic Systems, 2020, 97(1): 155-170. |
[45] |
Wang Y X, Zhang T, Cai Z H, et al. Multi-UAV coordination control by chaotic grey wolf optimization based distributed MPC with event-triggered strategy[J]. Chinese Journal of Aeronautics, 2020, 33(11): 2877-2897.
DOI URL |
[46] |
Hafez A T, Givigi S N, Yousefi S. Unmanned aerial vehicles formation using learning based model predictive control[J]. Asian Journal of Control, 2018, 20(3): 1014-1026.
DOI URL |
[47] |
Zhang B Y, Sun X X, Liu S G, et al. Distributed fault tolerant model predictive control for multi-unmanned aerial vehicle system[J]. Asian Journal of Control, 2022, 24(3): 1273-1292.
DOI URL |
[48] |
Spears W M, Spears D F, Hamann J C, et al. Distributed, physics-based control of swarms of vehicles[J]. Autonomous Robots, 2004, 17(2-3): 137-162.
DOI URL |
[49] | Kerr W, Spears D, Spears W, et al. Two formal gas models for multi-agent sweeping and obstacle avoidance[M]//Formal Approaches to Agent-based Systems. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004: 111-130. |
[50] | 沈林成, 王祥科, 朱华勇, 等. 基于拟态物理法的无人机集群与重构控制[J]. 中国科学(技术科学), 2017, 47(3): 266-285. |
[51] | Wang X, Wang X K, Zhang D B, et al. A liquid sphere-inspired physicomimetics approach for multiagent formation control[J]. International Journal of Robust and Nonlinear Control, 2018, 28(5): 4565-4583. |
[52] |
Luo Q N, Duan H B. An improved artificial physics approach to multiple UAVs/UGVs heterogeneous coordination[J]. Science China Technological Sciences, 2013, 56(10): 2473-2479.
DOI URL |
[53] |
Innocenti M, Pollini L, Giulietti F. Management of communication failures in formation flight[J]. Journal of Aerospace Computing, Information, and Communication, 2004, 1(1): 19-35.
DOI URL |
[54] |
Hao L, Qi X H, Yang Z H. Topology optimised fixed-time consensus for multi-UAV system in a multipath fading channel[J]. IET Communications, 2020, 14(11): 1730-1738.
DOI URL |
[55] |
Seo J, Kim Y, Kim S, et al. Consensus-based reconfigurable controller design for unmanned aerial vehicle formation flight[J]. Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering, 2012, 226(7): 817-829.
DOI URL |
[56] | 马小山, 董文瀚, 李炳乾. 考虑拓扑故障的无人机编队容错控制方法研究[J]. 西北工业大学学报, 2020, 38(5): 1084-1093. |
[57] | 林伯先. 复杂约束条件下多智能体系统鲁棒一致性跟踪控制研究[D]. 成都: 电子科技大学, 2020. |
[58] | Yu Z Q, Zhang Y M, Jiang B, et al. A review on fault-tolerant cooperative control of multiple unmanned aerial vehicles[J]. Chinese Journal of Aeronautics, 2022, 35(1): 1-18, 492. |
[59] |
Chen B S, Wang C P, Lee M Y. Stochastic robust team tracking control of multi-UAV networked system under Wiener and Poisson random fluctuations[J]. IEEE Transactions on Cybernetics, 2021, 51(12): 5786-5799.
DOI URL |
[60] | Liu C, Jiang B, Zhang K. Adaptive fault-tolerant H-infinity output feedback control for lead-wing close formation flight[J]. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2020, 50(8): 2804-2814. |
[61] |
Meissen C, Klausen K, Arcak M, et al. Passivity-based formation control for UAVs with a suspended load[J]. IFAC-PapersOnLine, 2017, 50(1): 13150-13155.
DOI URL |
[62] |
Wang X K, Yu Y G, Li Z K. Distributed sliding mode control for leader-follower formation flight of fixed- wing unmanned aerial vehicles subject to velocity constraints[J]. International Journal of Robust and Nonlinear Control, 2021, 31(6): 2110-2125.
DOI URL |
[63] |
Guo Y, Song D Y, Wang C Q, et al. Robust formation control for missiles with obstacle avoidance[J]. Chinese Journal of Aeronautics, 2022, 35(1): 70-80.
DOI URL |
[64] | 李一波, 胡杨, 陈伟, 等. 基于自抗扰控制技术的无人机编队控制器设计[J]. 飞行力学, 2015, 33(3): 205-208. |
[65] | Negash L, Kim S H, Choi H L. Distributed unknown-input-observers for cyber attack detection and isolation in formation flying UAVs[DB/OL]. arXiv Preprint: 1701.06325, 2017. |
[66] |
Wang D D, Zong Q, Tian B L, et al. Finite-time fully distributed formation reconfiguration control for UAV helicopters[J]. International Journal of Robust and Nonlinear Control, 2018, 28(18): 5943-5961.
DOI URL |
[67] |
Zhang Q R, Liu H H T. UDE-based robust command filtered backstepping control for close formation flight[J]. IEEE Transactions on Industrial Electronics, 2018, 65(11): 8818-8827.
DOI URL |
[68] | Xu Q, Yang H, Jiang B, et al. Fault tolerant formations control of UAVs subject to permanent and intermittent faults[J]. Journal of Intelligent & Robotic Systems, 2014, 73(1): 589-602. |
[69] |
Zhao X Y, Zong Q, Tian B L, et al. Finite-time fault-tolerant formation control for multiquadrotor systems with actuator fault[J]. International Journal of Robust and Nonlinear Control, 2018, 28(17): 5386-5405.
DOI URL |
[70] | Yu Z Q, Qu Y H, Zhang Y M, et al. Distributed adaptive fault-tolerant cooperative control for multi-UAVs against actuator and sensor faults[C]// Proceedings of ASME 2017 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. New York: ASME, 2017: DETC 2017-67637. |
[71] |
Yu Z Q, Qu Y H, Zhang Y M. Safe control of trailing UAV in close formation flight against actuator fault and wake vortex effect[J]. Aerospace Science and Technology, 2018, 77: 189-205.
DOI URL |
[72] |
Yu X, Liu Z X, Zhang Y M. Fault-tolerant formation control of multiple UAVs in the presence of actuator faults[J]. International Journal of Robust and Nonlinear Control, 2016, 26(12): 2668-2685.
DOI URL |
[73] |
Li P, Yu X, Peng X Y, et al. Fault-tolerant cooperative control for multiple UAVs based on sliding mode techniques[J]. Science China Information Sciences, 2017, doi: 10.1007/s11432-016-9074-8.
DOI |
[74] |
Liu D Y, Liu H, Xi J X. Fully distributed adaptive fault-tolerant formation control for octorotors subject to multiple actuator faults[J]. Aerospace Science and Technology, 2021, doi: 10.1016/j.ast.2020.106366.
DOI |
[75] |
Zheng Z, Qian M S, Li P, et al. Distributed adaptive control for UAV formation with input saturation and actuator fault[J]. IEEE Access, 2019, 7: 144638-144647.
DOI URL |
[76] |
Ma X S, Dong W H, Li B Q. Comprehensive fault-tolerant control of leader-follower unmanned aerial vehicles (UAVs) formation[J]. International Journal of Robotics and Automation, 2019, doi: 10.2316/J.2019.206-0301.
DOI |
[77] | Yang K, Sukkarieh S. Real-time continuous curvature path planning of UAVS in cluttered environments[C]// 2008 5th International Symposium on Mechatronics and its Applications. Piscataway: IEEE Press, 2018: 1-6. |
[78] |
Aurenhammer F. Voronoi diagrams: A survey of a fundamental geometric data structure[J]. ACM Computing Surveys, 1991, 23(3): 345-405.
DOI URL |
[79] | Li X, Xie J, Cai M Y, et al. Path planning for UAV based on improved heuristic A* algorithm[C]// 2009 9th International Conference on Electronic Measurement & Instruments. Piscataway: IEEE Press, 2009: 488-493. |
[80] | Kim H, Jeong J, Kim N, et al. A study on 3D optimal path planning for quadcopter UAV based on D lite[C]// 2019 International Conference on Unmanned Aircraft Systems (ICUAS). Piscataway:IEEE Press, 2019: 787-793. |
[81] |
Alkebsi K, Du W L. A fast multi-objective particle swarm optimization algorithm based on a new archive updating mechanism[J]. IEEE Access, 2020, 8: 124734-124754.
DOI URL |
[82] |
Shorakaei H, Vahdani M, Imani B, et al. Optimal cooperative path planning of unmanned aerial vehicles by a parallel genetic algorithm[J]. Robotica, 2016, 34(4): 823-836.
DOI URL |
[83] | Li B, Gong L G, Yang W L. An improved artificial bee colony algorithm based on balance-evolution strategy for unmanned combat aerial vehicle path planning[J]. The Scientific World Journal, 2014, 2014: 1-10. |
[84] | Wu H, Jagannathan S. Adaptive neural network control and wireless sensor network-based localization for UAV formation[C]// 2006 14th Mediterranean Conference on Control and Automation. Piscataway: IEEE Press, 2006: 1-6. |
[85] |
Wu X D, Bai W B, Xie Y E, et al. A hybrid algorithm of particle swarm optimization, metropolis criterion and RTS smoother for path planning of UAVs[J]. Applied Soft Computing, 2018, 73: 735-747.
DOI URL |
[86] | Li S D, Ding M Y, Cai C, et al. Efficient path planning method based on genetic algorithm combining path network[C]// 2010 Fourth International Conference on Genetic and Evolutionary Computing. Piscataway: IEEE Press, 2010: 194-197. |
[87] |
Shahrabi J, Khameneh S M. Application of a hybrid system of probabilistic neural networks and artificial bee colony algorithm for prediction of brand share in the market[J]. Industrial Engineering and Management Systems, 2016, 15(4): 324-334.
DOI URL |
[88] | Yu Z, Yang J Z, Chen S F, et al. Decentralized cooperative trajectory planning for multiple UAVs in dynamic and uncertain environments[C]// 2015 IEEE Seventh International Conference on Intelligent Computing and Information Systems. Piscataway: IEEE Press, 2015: 377-382. |
[89] | Zhen Z Y, Gao C, Zhao Q N, et al. Cooperative path planning for multiple UAVs formation[C]// The 4th Annual IEEE International Conference on Cyber Technology in Automation, Control and Intelligent. Piscataway: IEEE Press, 2014: 469-473. |
[90] |
Ryoo C K, Kim Y H, Tahk M J. Optimal UAV formation guidance laws with timing constraint[J]. International Journal of Systems Science, 2006, 37(6): 415-427.
DOI URL |
[91] | 赵恩娇, 孙明玮. 多飞行器协同作战关键技术研究综述[J]. 战术导弹技术, 2020(4): 175-182. |
[92] | 周佳玲. 多导弹系统同时命中目标的导引律设计研究[D]. 北京: 北京大学, 2016. |
[93] | 张艳秋. 带攻击角度和时间约束的制导方法研究[D]. 北京: 北京理工大学, 2016. |
[94] | Kumar S R, Ghose D. Sliding mode control based guidance law with impact time constraints[C]// 2013 American Control Conference. Piscataway: IEEE Press, 2013: 5760-5765. |
[95] | 李文, 李华滨, 王亮, 等. 多约束条件下导弹协同作战三维制导律设计[J]. 航天控制, 2018, 36(4): 12-18. |
[96] | 肖念远, 王晓芳, 周健. 多弹协同拦截制导律设计[J]. 弹箭与制导学报, 2020, 40(6): 20-25. |
[97] | 刘悦, 张佳梁, 赵利娟, 等. 基于二阶滑模控制的多导弹协同制导律研究[J]. 空天防御, 2020, 3(3): 83-88. |
[98] | 马骏, 马清华, 王根, 等. 基于伪谱法的多导弹协同攻击研究[J]. 计算机测量与控制, 2017, 25(1): 94-97. |
[99] | 吴亚霄. 基于一致性理论的多导弹协同制导研究[D]. 哈尔滨: 哈尔滨工业大学, 2017. |
[100] | 毛宁, 范军芳, 李斌. 基于快速一致性理论的多导弹协同制导[J]. 兵器装备工程学报, 2021, 42(5): 227-234. |
[101] |
Zhang P, Liu H H T, Li X B, et al. Fault tolerance of cooperative interception using multiple flight vehicles[J]. Journal of the Franklin Institute, 2013, 350(9): 2373-2395.
DOI URL |
[102] |
吕腾, 吕跃勇, 李传江, 等. 带视线角约束的多导弹有限时间协同制导律[J]. 兵工学报, 2018, 39(2): 305-314.
DOI |
[103] | 吕腾, 李传江, 郭延宁, 等. 有向拓扑下无径向速度测量的多导弹协同制导[J]. 宇航学报, 2018, 39(11): 1238-1247. |
[104] | 赵久奋, 史绍琨, 崇阳, 等. 带落角约束的多导弹分布式协同制导律[J]. 中国惯性技术学报, 2018, 26(4): 546-553. |
[105] | 段海滨, 邱华鑫, 陈琳, 等. 无人机自主集群技术研究展望[J]. 科技导报, 2018, 36(21): 90-98. |
[106] | 轩书哲, 周昊, 柯良军. 无人机集群对抗博弈综述[J]. 指挥信息系统与技术, 2021, 12(2): 27-31. |
[107] |
Chin H H. Knowledge-based system of supermaneuver selection for pilot aiding[J]. Journal of Aircraft, 1989, 26(12): 1111-1117.
DOI URL |
[108] | 钟麟, 佟明安, 钟卫, 等. 基于粗糙集-神经网络编队协同空战决策系统[J]. 火力与指挥控制, 2007, 32(5): 64-66. |
[109] |
Hu J Q, Wu H S, Zhan R J, et al. Self-organized search-attack mission planning for UAV swarm based on wolf pack hunting behavior[J]. Journal of Systems Engineering and Electronics, 2021, 32(6): 1463-1476.
DOI URL |
[110] |
Bonnet A, Akhloufi M A, Arola S. Drones chasing drones: Reinforcement learning and deep search area proposal[J]. Drones, 2019, doi: 10.3390/drones3030058.
DOI |
[111] |
Zhang J D, Yang Q M, Shi G Q, et al. UAV cooperative air combat maneuver decision based on multi-agent reinforcement learning[J]. Journal of Systems Engineering and Electronics, 2021, 32(6): 1421-1438.
DOI URL |
[112] | 朱建文, 赵长见, 李小平, 等. 基于强化学习的集群多目标分配与智能决策方法[J]. 兵工学报, 2021, 42(9): 2040-2048. |
[113] | DARPA Public Affairs. OFFSET envisions swarm capabilities for small urban ground units[EB/OL]. (2012-12-07)[2022-10-20]. https://www.darpa.mil/news-events/2016-12-07. |
[114] |
Zhang Y M, Jiang J. Bibliographical review on reconfigurable fault-tolerant control systems[J]. Annual Reviews in Control, 2008, 32(2): 229-252.
DOI URL |
[115] | 王杰东, 刘北, 董强健. 美国防部《无人系统综合路线图》分析[J]. 飞航导弹, 2019(5): 30-33. |
[116] | 机器人学国家重点实验室自主机器人课题组. 国家重点研发计划项目“警用无人平台关键技术研究及应用示范”项目开展应用示范[EB/OL]. (2021-04-28)[2022-10-20]. http://www.sia.cn/ar/xwdt/kydtz/202104/t20210428_6001188.html. |
[117] | 蔡亚梅, 宁勇, 郭涛. 美军有人-无人协同作战发展与趋势分析[J]. 航天电子对抗, 2021, 37(1): 12-18. |
[118] | 李磊, 王彤, 蒋琪. 美国CODE项目推进分布式协同作战发展[J]. 无人系统技术, 2019, 1(3): 59-66. |
[119] |
Zhao C H, Zhou Y H, Lin Z, et al. Review of scene matching visual navigation for unmanned aerial vehi-cles[J]. Scientia Sinica Informationis, 2019, 49(5): 507-519.
DOI URL |
[120] | Nam D V, Gon-Woo K. Solid-state LiDAR based-SLAM: A concise review and application[C]// 2021 IEEE International Conference on Big Data and Smart Computing (BigComp). Piscataway:IEEE Press, 2021: 302-305. |
[1] | SONG Zhengyu, HUANG Bing, WANG Xiaowei, ZHANG Hongjian, WANG Cong, ZHUANG Fangfang. Development and Key Technologies of Reusable Launch Vehicle [J]. Science and Technology Foresight, 2022, 1(1): 62-74. |
Viewed | ||||||
Full text |
|
|||||
Abstract |
|
|||||
京公网安备 11010802038735号