| Citation: | LIU Feng, WEI Ruixuan, ZHOU Kai, et al. Multi-UAV round up strategy based on unity of group will[J]. Journal of Beijing University of Aeronautics and Astronautics, 2022, 48(11): 2241-2249. doi: 10.13700/j.bh.1001-5965.2021.0109(in Chinese)
|
To solve the problem of unmanned aerial vehicle (UAV) coordinated rounding up, a strategy was proposed based on the unity of group will. Inspired by the cognitive mechanism of human beings in collaborative tasks, this paper introduces "group will" to define the collaborative cognition of UAVs, builds a double-loop cognitive model, and integrates the cognition of the local situation acquired by the rounded up UAVs with the help of the graph convolutional network, so as to effectively reduce the computing load of UAVs. On the basis of the variational inference principle and generative autoencoder, the group will convergence learning is carried out on the UAV, and the coordinated rounding up is realized on the basis of the Apollonius circle so that the UAV cluster emerges a more intelligent rounding up effect. The simulation results show the effectiveness and intelligence of the designed rounding up strategy.
| [1] |
段海滨, 申燕凯, 赵彦杰, 等. 2019年无人机热点回眸[J]. 科技导报, 2020, 38(1): 170-187. https://www.cnki.com.cn/Article/CJFDTOTAL-KJDB202001018.htm
DUAN H B, SHEN Y K, ZHAO Y J, et al. Review of technological hotspots of unmanned aerial vehicle in 2019[J]. Science Technology Review, 2020, 38(1): 170-187(in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-KJDB202001018.htm
|
| [2] |
段海滨, 张岱峰, 范彦铭, 等. 从狼群智能到无人机集群协同决策[J]. 中国科学: 信息科学, 2019, 49(1): 112-118. https://www.cnki.com.cn/Article/CJFDTOTAL-PZKX201901008.htm
DUAN H B, ZHANG D F, FAN Y M, et al. From wolf pack intelligence to UAV swarm cooperative decisionmaking[J]. Scientia Sinica: Informationis, 2019, 49(1): 112-118(in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-PZKX201901008.htm
|
| [3] |
ALEXOPOULOS A, SCHMIDT T, BADREDDIN E. A pursuit-evasion game between unmanned aerial vehicles[C]//2014 11th International Conference on Informatics in Control, Automation and Robotics (ICINCO). Piscataway: IEEE Press, 2014: 74-81.
|
| [4] |
吴子沉, 胡斌. 基于态势认知的无人机集群围捕方法[J]. 北京航空航天大学学报, 2021, 47(2): 424-430. https://www.cnki.com.cn/Article/CJFDTOTAL-BJHK202102029.htm
WU Z C, HU B. Swarm rounding up method of UAV based on situation cognition[J]. Journal of Beijing University of Aeronautics and Astronautics, 2021, 47(2): 424-430(in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-BJHK202102029.htm
|
| [5] |
YASUYUKI S, HIROFUMI O, TADASHI M, et al. Cooperative capture by multi-agent using reinforcement learning application for security patrol systems[C]//2015 10th Asian Control Conference (ASCC). Piscataway: IEEE Press, 2015: 1-6.
|
| [6] |
陈志鹏, 李健. 基于动物集群行为的无人机群目标围捕策略[J]. 现代计算机, 2018(2): 11-14. https://www.cnki.com.cn/Article/CJFDTOTAL-XDJS201806004.htm
CHEN Z P, LI J. Cluster UAVs hunting strategy based on biological collective behaviors[J]. Modern Computer, 2018(2): 11-14(in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-XDJS201806004.htm
|
| [7] |
蔡云飞, 唐振民, 张浩峰. 基于Cross-EKF定位的多机器人协作围捕策略研究[J]. 控制与决策, 2010, 25(9): 1313-1317. https://www.cnki.com.cn/Article/CJFDTOTAL-KZYC201009008.htm
CAI Y F, TANG Z M, ZHANG H F. Multi-robots cooperative hunting strategy based on Cross-EKF localization[J]. Control and Decision, 2010, 25(9): 1313-1317(in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-KZYC201009008.htm
|
| [8] |
黄天云, 陈雪波, 徐望宝, 等. 基于松散偏好规则的群体机器人系统自组织协作围捕[J]. 自动化学报, 2013, 39(1): 57-68. https://www.cnki.com.cn/Article/CJFDTOTAL-MOTO201301008.htm
HUANG T Y, CHEN X B, XU W B, et al. A self-organizing cooperative hunting by swarm robotic systems based on loose-preference rule[J]. Acta Automatica Sinica, 2013, 39(1): 57-68(in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-MOTO201301008.htm
|
| [9] |
李瑞珍, 杨惠珍, 萧丛杉. 基于动态围捕点的多机器人协同策略[J]. 控制工程, 2019, 26(3): 510-514. https://www.cnki.com.cn/Article/CJFDTOTAL-JZDF201903017.htm
LI R Z, YANG H Z, XIAO C S. Cooperative hunting strategy for multi-mobile robot systems based on dynamic hunting points[J]. Control Engineering of China, 2019, 26(3): 510-514(in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-JZDF201903017.htm
|
| [10] |
裴惠琴, 陈世明, 孙红伟. 动态环境下可扩展移动机器人群体的围捕控制[J]. 信息与控制, 2009, 38(4): 437-443. https://www.cnki.com.cn/Article/CJFDTOTAL-XXYK200904009.htm
PEI H Q, CHEN S M, SUN H W. Pursuit control of scalable swarm system of mobile robots in dynamic environment[J]. Information and Control, 2009, 38(4): 437-443(in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-XXYK200904009.htm
|
| [11] |
MURO C, ESCOBEDO R, SPECTOR L, et al. Wolf-pack (Canis lupus) hunting strategies emerge from simple rules in computational simulations[J]. Behavioural Processes, 2011, 88(3): 192-197.
|
| [12] |
LOWE R, WU Y, TAMAR A, et al. Multi-agent actor-critic for mixed cooperative-competitive environments[EB/OL]. (2017-06-07)[2021-02-14]. https://arxiv.org/abs/1706.02275v1.
|
| [13] |
MAO H Y, LIU W L, HAO J Y, et al. Neighborhood cognition consistent multi-agent reinforcement learning[J]. Proceedings of the AAAI Conference on Artificial Intelligence, 2020, 34(5): 7219-7226.
|
| [14] |
LIANG L, DENG F, PENG Z H, et al. A differential game for cooperative target defense[J]. Automatica, 2019, 102: 58-71.
|
| [15] |
KIPF T N, WELLING M. Semi-supervised classification with graph convolutional networks[C]//International Conference on Learning Representations (ICLR 2017), 2017: 1-14.
|
| [16] |
IOFFE S, SZEGEDY C. Batch normalization: Accelerating deep network training by reducing internal covariate shift[C]//Proceedings of the 32nd International Conference on International Conference on Machine Learning, 2015, 37: 448-456.
|
| [17] |
WU Z, PAN S, CHEN F, et al. A comprehensive survey on graph neural networks[J]. IEEE Transactions on Neural Networks and Learning Systems, 2021, 32(1): 4-24.
|
| [18] |
BLEI D M, KUCUKELBIR A, MCAULIFFE J D. Variational inference: A review for statisticians[J]. Journal of the American Statistical Association, 2017, 112(518): 859-877.
|
| [19] |
NAIR A, PONG V, DALAL M, et al. Visual reinforcement learning with imagined goals[EB/OL]. (2018-07-12)[2020-12-04]. https://arxiv.org/abs/1807.04742.
|
Figures(12) / Tables(1)
Copyright © Journal of Beijing University of Aeronautics and Astronautics
Address: Editorial Department of Journal of Beijing University of Aeronautics and Astronautics, 37 Xueyuan Road, Haidian District, Beijing Post Code: 100191 Email: jbuaa@buaa.edu.cn
Supported by:
Beijing Renhe Information Technology Co., Ltd.
DownLoad:
