Analysis of Multi-Robot Cooperative Hunting Using Differential Game Technique
Keywords:
Differential Game, Robot, Hunting Game, Pursuer, EvaderAbstract
This research presents two robots cooperative hunting behavior by the use of a differential game method. There are two pursuer robots that are trying to find and then surround another robot prey evader. The purpose of the game is for the two pursuer robots to find the evader simultaneously or when one of the robots finds the evader first it will wait for the other robot to cooperate with it within a specified period of time. We use differential game theory to formulate the problem with a system of an ordinary differential equation. The conditions for the termination of the game were given to be when one of the pursuers catch the evader and the other cooperate with it or when the two pursuers catch it simultaneously. We carefully analyzed all the mathematical equations developed using the ordinary differential equations for the game and present the sufficient conditions that can warrant the two pursuers to catch the evader either simultaneously or one first and then the other cooperates with the first one which will result in termination of the game. We also show mathematically that in the course of the game the robot prey evader tries to prolong the capture time, while the pursuer robots try to shorten the capture time
References
Azamov, A. A., & Samatov, B. (2000). π-strategy. An elementary introduction to the theory of differential games. Taskent: National Univ. of Uzb.
Berkovitz, L. (1974). Differential games. IEEE Transactions on Automatic Control, 19(5), 630–631. https://doi.org/10.1109/TAC.1974.1100627
Berkovitz, L. D. (1967). A survey of differential games, mathematical theory of control, eds. AV Balakrishnan and LW Neustadt. Academic Press, New York.
Burgard, W., Moors, M., Fox, D., Simmons, R., & Thrun, S. (2000). Collaborative multi-robot exploration. In Proceedings - IEEE International Conference on Robotics and Automation (Vol. 1, pp. 476–481). IEEE. https://doi.org/10.1109/robot.2000.844100
Davoodi, M., Faryadi, S., & Velni, J. M. (2021). A Graph Theoretic-Based Approach for Deploying Heterogeneous Multi-agent Systems with Application in Precision Agriculture. Journal of Intelligent and Robotic Systems: Theory and Applications, 101(1). https://doi.org/10.1007/s10846-020-01263-4
Fox, D., Burgard, W., Kruppa, H., & Thrun, S. (2000). Probabilistic approach to collaborative multi-robot localization. Autonomous Robots, 8(3), 325–344. https://doi.org/10.1023/A:1008937911390
Garcia, E., Casbeer, D. W., Von Moll, A., & Pachter, M. (2021). Multiple Pursuer Multiple Evader Differential Games. IEEE Transactions on Automatic Control, 66(5), 2345–2350. https://doi.org/10.1109/TAC.2020.3003840
Grinikh, A. L., & Petrosyan, L. A. (2021). AN EFFECTIVE PUNISHMENT for AN n-PERSON PRISONER’S DILEMMA on A NETWORK. Trudy Instituta Matematiki i Mekhaniki UrO RAN, 27(3), 256–262. https://doi.org/10.21538/0134-4889-2021-27-3-256-262
Gualtieri, L., Rauch, E., & Vidoni, R. (2021). Emerging research fields in safety and ergonomics in industrial collaborative robotics: A systematic literature review. Robotics and Computer-Integrated Manufacturing, 67, 101998. https://doi.org/10.1016/j.rcim.2020.101998
Helbing, D. (2010). Quantitative sociodynamics: Stochastic methods and models of social interaction processes. In Quantitative Sociodynamics: Stochastic Methods and Models of Social Interaction Processes (pp. 1–333). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-11546-2
Ibragimov, G., Ferrara, M., Kuchkarov, A., & Pansera, B. A. (2018). Simple Motion Evasion Differential Game of Many Pursuers and Evaders with Integral Constraints. Dynamic Games and Applications, 8(2), 352–378. https://doi.org/10.1007/s13235-017-0226-6
Ibragimov, G. I. (2003). Collective pursuit with integral constraints on the controls of players. Matematicheskie Trudy, 6(2), 66–79.
Ibragimov, G. I. (2005). Optimal pursuit with countably many pursuers and one evader. Differential Equations, 41(5), 627–635. https://doi.org/10.1007/s10625-005-0198-y
Ibragimov, G. I., Azamov, A. A., & Khakestari, M. (2011). Solution of a linear pursuit-evasion game with integral constraints. ANZIAM Journal, 51, 59. https://doi.org/10.21914/anziamj.v52i0.3605
Ibragimov, G. I., Salimi, M., & Amini, M. (2012). Evasion from many pursuers in simple motion differential game with integral constraints. European Journal of Operational Research, 218(2), 505–511. https://doi.org/10.1016/j.ejor.2011.11.026
Leong, W. J., & Ibragimov, G. I. (2008). A multiperson pursuit problem on a closed convex set in Hilbert space. Far East Journal of Applied Mathematics, 33(2), 205–214.
Moulin-Frier, C., & Oudeyer, P. Y. (2013). Exploration strategies in developmental robotics: A unified probabilistic framework. In 2013 IEEE 3rd Joint International Conference on Development and Learning and Epigenetic Robotics, ICDL 2013 - Electronic Conference Proceedings. IEEE. https://doi.org/10.1109/DevLrn.2013.6652535
Nehmzow, U. (2006). Scientific methods in mobile robotics: Quantitative analysis of agent behaviour. In Scientific Methods in Mobile Robotics: Quantitative Analysis of Agent Behaviour (pp. 1–207). Springer-Verlag. https://doi.org/10.1007/1-84628-260-8
Nighot, M. K., Patil, V. H., & Mani, G. S. (2012). Multi-robot hunting based on Swarm Intelligence. In Proceedings of the 2012 12th International Conference on Hybrid Intelligent Systems, HIS 2012 (pp. 203–206). IEEE. https://doi.org/10.1109/HIS.2012.6421334
Parsa, S., & Saadat, M. (2021). Human-robot collaboration disassembly planning for end-of-life product disassembly process. Robotics and Computer-Integrated Manufacturing, 71, 102170. https://doi.org/10.1016/j.rcim.2021.102170
Pontryagin, L. S. (1988). Collected works. Nauka, Moscow.
Rikhsiev, B. B. (1989). The differential games with simple motions. Tashkent: Fan.
Schaal, S., & Atkeson, C. G. (2010). Learning control in robotics. IEEE Robotics and Automation Magazine, 17(2), 20–29. https://doi.org/10.1109/MRA.2010.936957
Stone, P., & Veloso, M. (2000). Multiagent systems: a survey from a machine learning perspective. In Autonomous Robots (Vol. 8, Issue 3). Defense Technical Information Center. https://doi.org/10.1023/A:1008942012299
Subbotin, A. I., & Chentsov, A. G. (1981). Optimization of guarantee in control problems. Hauka. Moscow (in Rus-Sian), 288.
Teslya, N., Smirnov, A., Ionov, A., & Kudrov, A. (2021). Multi-robot coalition formation for precision agriculture scenario based on gazebo simulator. In Smart Innovation, Systems and Technologies (Vol. 187, pp. 329–341). Springer Singapore. https://doi.org/10.1007/978-981-15-5580-0_27
Thrun, S. (2000). Probabilistic algorithms in robotics. AI Magazine, 21(4), 93–109.
Vajda, S. (1967). Differential Games. A Mathematical Theory with Applications to Warfare and Pursuit, Control and Optimization. By Rufus Isaacs. Pp. xxii, 384. 113s. 1965. (Wiley). The Mathematical Gazette, 51(375), 80–81. https://doi.org/10.2307/3613661
Varghese, B., & McKee, G. T. (2009). Modeling and simulating a mathematical tool for multi-robot pattern transformation. In Proceedings - 2009 International Conference on Computer Modeling and Simulation, ICCMS 2009 (pp. 21–27). IEEE. https://doi.org/10.1109/ICCMS.2009.40