A journal of IEEE and CAA , publishes high-quality papers in English on original theoretical/experimental research and development in all areas of automation
Volume 11 Issue 2
Feb.  2024

IEEE/CAA Journal of Automatica Sinica

  • JCR Impact Factor: 11.8, Top 4% (SCI Q1)
    CiteScore: 17.6, Top 3% (Q1)
    Google Scholar h5-index: 77, TOP 5
Turn off MathJax
Article Contents
N. Chen, L. Li, and  W.  Mao,  “Equilibrium strategy of the pursuit-evasion game in three-dimensional space,” IEEE/CAA J. Autom. Sinica, vol. 11, no. 2, pp. 446–458, Feb. 2024. doi: 10.1109/JAS.2023.123996
Citation: N. Chen, L. Li, and  W.  Mao,  “Equilibrium strategy of the pursuit-evasion game in three-dimensional space,” IEEE/CAA J. Autom. Sinica, vol. 11, no. 2, pp. 446–458, Feb. 2024. doi: 10.1109/JAS.2023.123996

Equilibrium Strategy of the Pursuit-Evasion Game in Three-Dimensional Space

doi: 10.1109/JAS.2023.123996
Funds:  This work was supported in part by the Strategic Priority Research Program of Chinese Academy of Sciences (XDA27030100), and National Natural Science Foundation of China (72293575, 11832001)
More Information
  • The pursuit-evasion game models the strategic interaction among players, attracting attention in many realistic scenarios, such as missile guidance, unmanned aerial vehicles, and target defense. Existing studies mainly concentrate on the cooperative pursuit of multiple players in two-dimensional pursuit-evasion games. However, these approaches can hardly be applied to practical situations where players usually move in three-dimensional space with a three-degree-of-freedom control. In this paper, we make the first attempt to investigate the equilibrium strategy of the realistic pursuit-evasion game, in which the pursuer follows a three-degree-of-freedom control, and the evader moves freely. First, we describe the pursuer’s three-degree-of-freedom control and the evader’s relative coordinate. We then rigorously derive the equilibrium strategy by solving the retrogressive path equation according to the Hamilton-Jacobi-Bellman-Isaacs (HJBI) method, which divides the pursuit-evasion process into the navigation and acceleration phases. Besides, we analyze the maximum allowable speed for the pursuer to capture the evader successfully and provide the strategy with which the evader can escape when the pursuer’s speed exceeds the threshold. We further conduct comparison tests with various unilateral deviations to verify that the proposed strategy forms a Nash equilibrium.

     

  • loading
  • [1]
    I. E. Weintraub, M. Pachter, and E. García, “An introduction to pursuit-evasion differential games,” in Proc. American Control Conf., 2020, pp. 1049–1066.
    [2]
    M. J. Osborne and A. Rubinstein, A Course in Game Theory. Cambridge, USA: MIT Press, 1994.
    [3]
    H. Huang, J. Ding, W. Zhang, and C. J. Tomlin, “Automation-assisted capture-the-flag: A differential game approach,” IEEE Trans. Control Systems Technology, vol. 23, no. 3, pp. 1014–1028, 2015. doi: 10.1109/TCST.2014.2360502
    [4]
    J. Shinar, M. Guelman, and A. Green, “An optimal guidance law for a planar pursuit-evasion game of kind,” Computers &Mathematics With Applications, vol. 18, no. 1−3, pp. 35–44, 1989.
    [5]
    V. Turetsky and J. Shinar, “Missile guidance laws based on pursuit-evasion game formulations,” Automatica, vol. 39, no. 4, pp. 607–618, 2003. doi: 10.1016/S0005-1098(02)00273-X
    [6]
    W. Li, Y. Zhu, and D. Zhao, “Missile guidance with assisted deep reinforcement learning for head-on interception of maneuvering target,” Complex &Intelligent Systems, vol. 8, no. 2, pp. 1205–1216, 2022.
    [7]
    J. Guo, Z. Wang, J. Lan, B. Dong, R. Li, Q. Yang, and J. Zhang, “Maneuver decision of UAV in air combat based on deterministic policy gradient,” in Proc. IEEE 17th Int. Conf. Control & Automation, 2022, pp. 243–248.
    [8]
    R. Vidal, S. Rashid, C. Sharp, O. Shakernia, K. Jin, and S. Sastry, “Pursuit-evasion games with unmanned ground and aerial vehicles,” in Proc. IEEE Int. Conf. Robotics and Automation, 2001, vol. 3, pp. 2948–2955.
    [9]
    Q. Yang, J. Zhang, G. Shi, J. Hu, and Y. Wu, “Maneuver decision of UAV in short-range air combat based on deep reinforcement learning,” IEEE Access, vol. 8, pp. 363–378, 2020. doi: 10.1109/ACCESS.2019.2961426
    [10]
    M. Chen, Z. Zhou, and C. J. Tomlin, “Multiplayer reach-avoid games via pairwise outcomes,” IEEE Trans. Autom. Control, vol. 62, no. 3, pp. 1451–1457, 2016.
    [11]
    E. Garcia, D. W. Casbeer, and M. Pachter, “Design and analysis of state-feedback optimal strategies for the differential game of active defense,” IEEE Trans. Autom. Control, vol. 64, no. 2, pp. 553–568, 2018.
    [12]
    S. Pan, H. Huang, J. Ding, W. Zhang, D. M. S. vić, and C. J. Tomlin, “Pursuit, evasion and defense in the plane,” in Proc. American Control Conf., 2012, pp. 4167–4173.
    [13]
    R. Isaacs, Differential Games: A Mathematical Theory With Applications to Warfare and Pursuit, Control and Optimization. Mineola, USA: John Wiley and Sons, Inc., 1965.
    [14]
    L. C. Evans, Partial Differential Equations. Providence, USA: American Mathematical Soc., 2010.
    [15]
    P. Hagedorn and J. Breakwell, “A differential game with two pursuers and one evader,” J. Optimization Theory and Applications, vol. 18, no. 1, pp. 15–29, 1976. doi: 10.1007/BF00933791
    [16]
    J. Breakwell and P. Hagedorn, “Point capture of two evaders in succession,” J. Optimization Theory and Applications, vol. 27, no. 1, pp. 89–97, 1979. doi: 10.1007/BF00933327
    [17]
    A. T. Bilgin and E. Kadioglu-Urtis, “An approach to multi-agent pursuit evasion games using reinforcement learning,” in Proc. Int. Conf. Advanced Robotics, 2015, pp. 164–169.
    [18]
    E. Bakolas and P. Tsiotras, “Relay pursuit of a maneuvering target using dynamic Voronoi diagrams,” Automatica, vol. 48, no. 9, pp. 2213–2220, 2012. doi: 10.1016/j.automatica.2012.06.003
    [19]
    Z. Zhou, W. Zhang, J. Ding, H. Huang, D. M. Stipanović, and C. J. Tomlin, “Cooperative pursuit with Voronoi partitions,” Automatica, vol. 72, pp. 64–72, 2016. doi: 10.1016/j.automatica.2016.05.007
    [20]
    J. Chen, W. Zha, Z. Peng, and D. Gu, “Multi-player pursuit-evasion games with one superior evader,” Automatica, vol. 71, pp. 24–32, 2016. doi: 10.1016/j.automatica.2016.04.012
    [21]
    M. Ramana and M. Kothari, “A cooperative pursuit-evasion game of a high speed evader,” in Proc. IEEE Conf. Decision and Control, 2015, pp. 2969–2974.
    [22]
    X. Fang, C. Wang, L. Xie, and J. Chen, “Cooperative pursuit with multi-pursuer and one faster free-moving evader,” IEEE Trans. Cyber., vol. 52, no. 3, pp. 1405–1414, 2022.
    [23]
    W. Zha, J. Chen, Z. Peng, and D. Gu, “Construction of barrier in a fishing game with point capture,” IEEE Trans. Cyber., vol. 47, no. 6, pp. 1409–1422, 2016.
    [24]
    E. Garcia, D. W. Casbeer, A. Von Moll, and M. Pachter, “Multiple pursuer multiple evader differential games,” IEEE Trans. Automatic Control, vol. 66, no. 5, pp. 2345–2350, 2020.
    [25]
    G. Hexner, “A differential game of incomplete information,” J. Optimization Theory and Applications, vol. 28, no. 2, pp. 213–232, 1979. doi: 10.1007/BF00933243
    [26]
    M. Pachter and Y. Yavin, “A stochastic homicidal chauffeur pursuit-evasion differential game,” J. Optimization Theory and Applications, vol. 34, no. 3, pp. 405–424, 1981. doi: 10.1007/BF00934680
    [27]
    Y. Yang and J. Wang, “An overview of multi-agent reinforcement learning from game theoretical perspective,” [Online], Available: https://arxiv.org/abs/2011.00583, 2020.
    [28]
    J. Selvakumar and E. Bakolas, “Min-max Q-learning for multi-player pursuit-evasion games,” Neurocomputing, vol. 475, pp. 1–14, 2022. doi: 10.1016/j.neucom.2021.12.025
    [29]
    R. Lowe, Y. Wu, A. Tamar, J. Harb, O. Pieter Abbeel, and I. Mordatch, “Multi-agent actor-critic for mixed cooperative-competitive environments,” in Proc. Advances in Neural Information Processing Systems, 2017, vol. 30, pp. 6379–6390.
    [30]
    Y. Wang, L. Dong, and C. Sun, “Cooperative control for multi-player pursuit-evasion games with reinforcement learning,” Neurocomputing, vol. 412, pp. 101–114, 2020. doi: 10.1016/j.neucom.2020.06.031
    [31]
    K. Wan, D. Wu, Y. Zhai, B. Li, X. Gao, and Z. Hu, “An improved approach towards multi-agent pursuit-evasion game decision-making using deep reinforcement learning,” Entropy, vol. 23, no. 11, p. 1433, 2021. doi: 10.3390/e23111433
    [32]
    Z. Zhou and H. Xu, “Decentralized optimal large scale multi-player pursuit-evasion strategies: A mean field game approach with reinforcement learning,” Neurocomputing, vol. 484, pp. 46–58, 2022. doi: 10.1016/j.neucom.2021.01.141
    [33]
    T. T. Nguyen, N. D. Nguyen, and S. Nahavandi, “Deep reinforcement learning for multiagent systems: A review of challenges, solutions, and applications,” IEEE Trans. Cyber., vol. 50, no. 9, pp. 3826–3839, 2020. doi: 10.1109/TCYB.2020.2977374
    [34]
    Y. Yang, L. Liao, H. Yang, and S. Li, “An optimal control strategy for multi-UAVs target tracking and cooperative competition,” IEEE/CAA J. Autom. Sinica, vol. 8, no. 12, pp. 1931–1947, 2021. doi: 10.1109/JAS.2020.1003012
    [35]
    N. Wen, L. Zhao, X. Su, and P. Ma, “UAV online path planning algorithm in a low altitude dangerous environment,” IEEE/CAA J. Autom. Sinica, vol. 2, no. 2, pp. 173–185, 2015. doi: 10.1109/JAS.2015.7081657
    [36]
    Z. Zuo, C. Liu, Q.-L. Han, and J. Song, “Unmanned aerial vehicles: Control methods and future challenges,” IEEE/CAA J. Autom. Sinica, vol. 9, no. 4, pp. 601–614, 2022. doi: 10.1109/JAS.2022.105410
    [37]
    T. Miloh, “A note on three-dimensional pursuit-evasion game with bounded curvature,” IEEE Trans. Automatic Control, vol. 27, no. 3, pp. 739–741, 1982. doi: 10.1109/TAC.1982.1102992
    [38]
    N. Greenwood, “A differential game in three dimensions: The aerial dogfight scenario,” Dynamics and Control, vol. 2, no. 2, pp. 161–200, 1992. doi: 10.1007/BF02169496
    [39]
    N. Rajan and M. Ardema, “Interception in three dimensions-an energy formulation,” J. Guidance,Control,and Dynamics, vol. 8, no. 1, pp. 23–30, 1985. doi: 10.2514/3.19930
    [40]
    F. Imado and T. Kuroda, “A method to solve missile-aircraft pursuit-evasion differential games,” IFAC Proceedings Volumes, vol. 38, no. 1, pp. 176–181, 2005.
    [41]
    Z. Hu, P. Gao, and F. Wang, “Research on autonomous maneuvering decision of UCAV based on approximate dynamic programming,” [Online], Available: https://arxiv.org/abs/1908.10010, 2019.
    [42]
    T. Başar and G. J. Olsder, Dynamic Noncooperative Game Theory. New York, USA: SIAM, 1998.
    [43]
    T. Başar, A. Haurie, and G. Zaccour, Nonzero-Sum Differential Games. Cham, Switzerland: Springer Int. Publishing, 2018, pp. 61–110.
    [44]
    P. L A, Differential Games Of Pursuit, ser. Series on Optimization, vol 2. Singapore: World Scientific, 1993.
    [45]
    D. Liberzon, Calculus of Variations and Optimal Control Theory: A Concise Introduction. USA: Princeton University Press, 2011.
    [46]
    X. Liao, C. Zhou, J. Wang, J. Fan, and Z. Zhang, “A wire-driven elastic robotic fish and its design and cpg-based control,” J. Intelligent &Robotic Systems, vol. 107, no. 1, p. 4, 2022.
    [47]
    J. Chai, W. Chen, Y. Zhu, Z. Yao, and D. Zhao, “A hierarchical deep reinforcement learning framework for 6-DoF UCAV air-to-air combat,” IEEE Trans. Systems,Man,and Cyber: Systems, vol. 53, no. 9, pp. 5417–5429, 2023. doi: 10.1109/TSMC.2023.3270444
    [48]
    G. Wu, S. Bai, and P. Hjørnet, “On the stiffness of three/four degree-of-freedom parallel pick-and-place robots with four identical limbs,” in Proc. IEEE Int. Conf. Robotics and Automation, 2016, pp. 861–866.

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Figures(11)  / Tables(3)

    Article Metrics

    Article views (300) PDF downloads(65) Cited by()

    Highlights

    • We make the first attempt to theoretically investigate the equilibrium strategy for the players conducting realistic motions in three-dimensional space
    • We derive the equilibrium strategy to tackle the realistic pursuit-evasion game by modeling the three-degree-of-freedom kinematics of the pursuer, which is typical in many real-world applications
    • We provide the theoretical derivation of the equilibrium strategy based on the HJBI equation to ensure the minimax property of the equilibrium strategy
    • We analyze the velocity threshold for a successful capture and then derive the optimal acceleration scheme for the pursuer and the escape strategy for the evader whenever the pursuer's speed exceeds the threshold
    • Our proposed solution supports real-time decisions for the pursuit-evasion games in the three-dimensional space

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return