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Competitive Two Team Target Search Game with Communication Symmetry and Asymmetry

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Algorithmic Foundations of Robotics XII

Part of the book series: Springer Proceedings in Advanced Robotics ((SPAR,volume 13))

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Abstract

We study a search game in which two multiagent teams compete to find a stationary target at an unknown location. Each team plays a mixed strategy over the set of search sweep-patterns allowed from its respective random starting locations. Assuming that communication enables cooperation we find closed-form expressions for the probability of winning the game as a function of team sizes, and vs. the existence or absence of communication within each team. Assuming the target is distributed uniformly at random, an optimal mixed strategy equalizes the expected first-visit time to all points within the search space. The benefits of communication enabled cooperation increase with team size. Simulations and experiments agree well with analytical results.

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References

  1. Beard, R.W., McLain, T.W.: Multiple uav cooperative search under collision avoidance and limited range communication constraints. In: Decision and Control, 2003. Proceedings. 42nd IEEE Conference on. vol. 1, pp. 25-30 Vol.1 (Dec 2003)

    Google Scholar 

  2. Bertuccelli, L.F., How, J.P.: Robust UAV search for environments with imprecise probability maps. In: IEEE Conf. on Decision and Control and the European Control Conferenc. pp. 5680-5685 (Dec 2005)

    Google Scholar 

  3. Bhattacharya, S., Khanafer, A., BaÅŸar, T.: A Double-Sided Jamming Game with Resource Constraints, pp. 209-227. Springer International Publishing (2016)

    Google Scholar 

  4. Chandler, P., Pachter, M.: Hierarchical control for autonomous teams. In: Proceedings of the AIAA Guidance, Navigation, and Control Conference. pp. 632-642 (2001)

    Google Scholar 

  5. Choset, H., Pignon, P.: Coverage path planning: The boustrophedon cellular decomposition. In: Field and Service Robotics. pp. 203-209. Springer (1998)

    Google Scholar 

  6. Chung, T.H., Hollinger, G.A., Isler, V.: Search and pursuit-evasion in mobile robotics. Auton. Robots 31(4), 299-316 (2011)

    Google Scholar 

  7. Demaine, E.D., Fekete, S.P., Gal, S.: Online searching with turn cost. Theoretical Computer Science 361(2), 342-355 (2006)

    Google Scholar 

  8. Dias, M.B., Zlot, R., Kalra, N., Stentz, A.: Market-based multirobot coordination: A survey and analysis. Proceedings of the IEEE 94(7), 1257-1270 ( 2006)

    Google Scholar 

  9. Dias, M.B.: Traderbots: A new paradigm for robust and efficient multirobot coordination in dynamic environments. Ph.D. thesis, Carnegie Mellon University Pittsburgh (2004)

    Google Scholar 

  10. Feinerman, O., Korman, A., Lotker, Z., Sereni, J.S.: Collaborative search on the plane without communication. In: Proceedings of the 2012 ACM Symposium on Principles of Distributed Computing. pp. 77-86. PODC ’12, ACM, New York, NY, USA (2012), https://doi.org/10.1145/2332432.2332444

  11. Flint, M., Polycarpou, M., Fernandez-Gaucherand, E.: Cooperative control for multiple autonomous uav’s searching for targets. In: Decision and Control, 2002, Proceedings of the 41st IEEE Conference on. vol. 3, pp. 2823-2828 vol.3 (Dec 2002)

    Google Scholar 

  12. Forsmo, E.J., Grotli, E.I., Fossen, T.I., Johansen, T.A.: Optimal search mission with unmanned aerial vehicles using mixed integer linear programming. In: Unmanned Aircraft Systems (ICUAS), 2013 International Conference on. pp. 253-259 (May 2013)

    Google Scholar 

  13. Gerkey, B.P., Thrun, S., Gordon, G.: Parallel stochastic hill-climbing with small teams. In: Multi-Robot Systems. From Swarms to Intelligent Automata Volume III, pp. 65-77. Springer (2005)

    Google Scholar 

  14. Hollinger, G.A., Yerramalli, S., Singh, S., Mitra, U., Sukhatme, G.S.: Distributed data fusion for multirobot search 31(1), 55-66 (2015)

    Google Scholar 

  15. Hu, J., Xie, L., Lum, K.Y., Xu, J.: Multiagent information fusion and cooperative control in target search 21(4), 1223-1235 (2013)

    Google Scholar 

  16. Huang, A.S., Olson, E., Moore, D.C.: Lcm: Lightweight communications and marshalling. In: Intelligent robots and systems (IROS), 2010 IEEE/RSJ international conference on. pp. 4057-4062. IEEE (2010)

    Google Scholar 

  17. Huang, H., Ding, J., Zhang, W., Tomlin, C.J.: Automation-assisted capture-the- flag: A differential game approach. IEEE Transactions on Control Systems Technology 23(3), 1014-1028 (2015)

    Google Scholar 

  18. Kim, M.H., Baik, H., Lee, S.: Response threshold model based uav search planning and task allocation. Journal of Intelligent & Robotic Systems 75(3), 625-640 (2013)

    Google Scholar 

  19. Koopman, B.: The theory of search. ii. target detection. Operations Research 4(5), 503-531 (1956)

    Google Scholar 

  20. Lynen, S., Achtelik, M.W., Weiss, S., Chli, M., Siegwart, R.: A robust and modular multi-sensor fusion approach applied to mav navigation. In: 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems. pp. 3923-3929 (Nov 2013)

    Google Scholar 

  21. Mangel, M.: Marcel Dekker, New York (1989)

    Google Scholar 

  22. Noori, N., Isler, V.: Lion and man with visibility in monotone polygons. The International Journal of Robotics Research p. 0278364913498291 (2013)

    Google Scholar 

  23. Sato, H., Royset, J.O.: Path optimization for the resource-constrained searcher. Naval Research Logistics 57(5), 422-440 (2010)

    Google Scholar 

  24. Spieser, K., Frazzoli, E.: The cow-path game: A competitive vehicle routing problem. In: Decision and Control (CDC), 2012 IEEE 51st Annual Conference on. pp. 6513-6520 (Dec 2012)

    Google Scholar 

  25. Spires, S.V., Goldsmith, S.Y.: Exhaustive geographic search with mobile robots along space-filling curves. In: Collective robotics, pp. 1-12. Springer (1998)

    Google Scholar 

  26. Sujit, P.B., Ghose, D.: Multiple agent search of an unknown environment using game theoretical models. In: American Control Conf. vol. 6, pp. 5564-5569 vol.6 (June 2004)

    Google Scholar 

  27. Sujit, P.B., Ghose, D.: Negotiation schemes for multi-agent cooperative search. Proc. of the Institution of Mech. Engineers, Part G: J. of Aero. Eng. 223(6), 791813 (2009)

    Google Scholar 

  28. Sydney, N., Paley, D.A., Sofge, D.: Physics-inspired motion planning for information-theoretic target detection using multiple aerial robots. Auton. Robots pp. 1-11 (2015)

    Google Scholar 

  29. Trummel, K., Weisinger, J.: Technical notethe complexity of the optimal searcher path problem. Operations Research 34(2), 324-327 (1986)

    Google Scholar 

  30. Vincent, P., Rubin, I.: A framework and analysis for cooperative search using UAV swarms. In: ACM Symposium on Applied Computing. pp. 79-86. SAC ’04, ACM, New York, NY, USA (2004), https://doi.org/10.1145/967900.967919

  31. Waharte, S., Trigoni, N.: Supporting search and rescue operations with UAVs. In: Int. Conf. on Emerging Security Technologies. pp. 142-147 (Sept 2010)

    Google Scholar 

  32. Zhu, M., Frazzoli, E.: On competitive search games for multiple vehicles. In: Decision and Control (CDC), 2012 IEEE 51st Annual Conference on. pp. 5798-5803 (Dec 2012)

    Google Scholar 

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Correspondence to Michael Otte .

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Otte, M., Kuhlman, M., Sofge, D. (2020). Competitive Two Team Target Search Game with Communication Symmetry and Asymmetry. In: Goldberg, K., Abbeel, P., Bekris, K., Miller, L. (eds) Algorithmic Foundations of Robotics XII. Springer Proceedings in Advanced Robotics, vol 13. Springer, Cham. https://doi.org/10.1007/978-3-030-43089-4_14

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