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Communication Papers of the 17th Conference on Computer Science and Intelligence Systems

Annals of Computer Science and Information Systems, Volume 32

A comprehensive framework for designing behavior of UAV swarms

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DOI: http://dx.doi.org/10.15439/2022F234

Citation: Communication Papers of the 17th Conference on Computer Science and Intelligence Systems, M. Ganzha, L. Maciaszek, M. Paprzycki, D. Ślęzak (eds). ACSIS, Vol. 32, pages 173180 ()

Full text

Abstract. This paper aims to present a method of designing the behavior of robotic swarms, emphasizing swarms of unmanned aerial vehicles using bigraphs. The method's primary goal is to define a set of actions to be performed in subsequent moments by the members of a swarm that lead to the completion of the given task. In addition to formal definitions, an example use case is also included to demonstrate how utilizing our method allows overcoming typical difficulties related to swarm robotics engineering. The example covers verifying non-functional requirements and scaling a task both horizontally and vertically.

References

  1. P. Cybulski, Z. Zieliński, “Design and Verification of Multi-Agent Systems with the Use of Bigraphs“, Applied Sciences, https://www.mdpi.com/2076-3417/11/18/8291, http://dx.doi.org/10.3390/app11188291
  2. P. Cybulski, Z. Zieliński, “UAV Swarms Behavior Modeling Using Tracking Bigraphical Reactive Systems“, Sensors, https://www.mdpi.com/1424-8220/21/2/622, http://dx.doi.org/10.3390/s21020622
  3. R. Milner, 2009, “The Space and Motion of Communicating Agents“, ISBN=978-0-521-73833-0, Cambridge University Press, http://dx.doi.org/10.1017/CBO9780511626661
  4. T. Sheridan, W. Verplank, “Human and Computer Control of Undersea Teleoperators“, 1978.
  5. S. Benford, M. Calder, T. Rodden, M. Sevegnani, “On Lions, Impala, and Bigraphs: Modelling Interactions in Physical/Virtual Spaces“, ACM Trans. Comput.-Hum. Interact., May 2016, http://dx.doi.org/10.1145/2882784
  6. J. Krivine, R. Milner, A. Troina, “Stochastic Bigraphs“, Electronic Notes in Theoretical Computer Science, year = 2008, https://www.sciencedirect.com/science/article/pii/S1571066108004003, http://dx.doi.org/10.1016/j.entcs.2008.10.006
  7. O. H. Jensen, “Mobile Processes in Bigraphs“, 2006, https://www.cl.cam.ac.uk/archive/rm135/Jensen-monograph.pdf.
  8. P. Stone, M. Veloso, Multiagent Systems: A Survey from a Machine Learning Perspective. Autonomous Robots 8, 345–383 (2000). http://dx.doi.org/10.1023/A:1008942012299
  9. H. Hamann. (2018). Swarm Robotics: A Formal Approach. http://dx.doi.org/10.1007/978-3-319-74528-2.
  10. Y. Mohan and S. G. Ponnambalam, "An extensive review of research in swarm robotics," 2009 World Congress on Nature & Biologically Inspired Computing (NaBIC), 2009, pp. 140-145, http://dx.doi.org/10.1109/NABIC.2009.5393617.
  11. Brambilla, Manuele & Ferrante, Eliseo & Birattari, Mauro & Dorigo, Marco. (2013). Swarm Robotics: A Review from the Swarm Engineering Perspective. Swarm Intelligence. 7. 1-41. http://dx.doi.org/10.1007/s11721-012-0075-2
  12. Navarro, Iñaki & Matía, Fernando. (2013). An Introduction to Swarm Robotics. ISRN Robotics. 2013. http://dx.doi.org/10.5402/2013/608164
  13. Iocchi, Luca & Nardi, Daniele & Salerno, Massimiliano & Hannebauer, Markus & Wendler, Jan & Pagello, Enrico. (2001). Reactivity and Deliberation: A Survey on Multi-Robot Systems. 2103. 9-32. http://dx.doi.org/10.1007/3-540-44568-4_2.
  14. Nedjah, Nadia & Silva Junior, Luneque. (2019). Review of methodologies and tasks in swarm robotics towards standardization. Swarm and Evolutionary Computation. 50. 100565. http://dx.doi.org/10.1016/j.swevo.2019.100565
  15. Bayindir, Levent. (2015). A Review of Swarm Robotics Tasks. Neurocomputing. 172. http://dx.doi.org/10.1016/j.neucom.2015.05.116
  16. Dudek, G., Jenkin, M.R., Parker, L.E., & Lin, L. (2003). A Taxonomy of Multirobot Systems.
  17. Crespi, V., Galstyan, A.G., & Lerman, K. (2008). Top-down vs bottom-up methodologies in multi-agent system design. Autonomous Robots, 24, 303-313.
  18. A. Kolling, P. Walker, N. Chakraborty, K. Sycara and M. Lewis, "Human Interaction With Robot Swarms: A Survey," in IEEE Transactions on Human-Machine Systems, vol. 46, no. 1, pp. 9-26, Feb. 2016, http://dx.doi.org/10.1109/THMS.2015.2480801
  19. Valentini, Gabriele. (2017). Achieving Consensus in Robot Swarms. http://dx.doi.org/10.1007/978-3-319-53609-5
  20. Francesca, Gianpiero & Brambilla, Manuele & Brutschy, Arne & Trianni, Vito & Birattari, Mauro. (2014). AutoMoDe: A novel approach to the automatic design of control software for robot swarms. Swarm Intell. 8. 1-24. http://dx.doi.org/10.1007/s11721-014-0092-4
  21. Brambilla, Manuele & Brutschy, Arne & Dorigo, Marco & Birattari, Mauro. (2014). Property-Driven Design for Robot Swarms. ACM Transactions on Autonomous and Adaptive Systems. 9. 1-28. http://dx.doi.org/10.1145/2700318
  22. E. Pereira, C. Potiron, C. M. Kirsch and R. Sengupta, "Modeling and controlling the structure of heterogeneous mobile robotic systems: A bigactor approach," 2013 IEEE International Systems Conference (SysCon), 2013, pp. 442-447, http://dx.doi.org/10.1109/SysCon.2013.6549920
  23. Bachrach, Jonathan & Mclurkin, James & Grue, Anthony. (2008). Protoswarm: A language for programming multi-robot systems using the amorphous medium abstraction. 2. 1175-1178.
  24. Pianini, D., Viroli, M., & Beal, J. (2015). Engineering multi-agent systems with aggregate computing.
  25. Byrski, Aleksander & Drezewski, Rafal & Siwik, Leszek & Kisiel-Dorohinicki, Marek. (2015). Evolutionary multi-agent systems. The Knowledge Engineering Review. 30. 171-186. http://dx.doi.org/10.1017/S0269888914000289
  26. Floreano, Dario & Mattiussi, Claudio. (2008). Bio-Inspired Artificial Intelligence: Theories, Methods, and Technologies. ISBN:978-0262062718
  27. Spears, William & Spears, Diana & Hamann, Jerry & Heil, Rodney. (2004). Distributed, Physics-Based Control of Swarms of Vehicles. Auton. Robots. 2. http://dx.doi.org/10.1023/B:AURO.0000033970.96785.f2
  28. Çelikkanat, Hande & Sahin, Erol. (2010). Steering self-organized robot flocks through externally guided individuals. Neural Computing and Applications. 19. 849-865. http://dx.doi.org/10.1007/s00521-010-0355-y
  29. J. Yu, S. M. LaValle and D. Liberzon, "Rendezvous Without Coordinates," in IEEE Transactions on Automatic Control, vol. 57, no. 2, pp. 421-434, Feb. 2012, http://dx.doi.org/10.1109/TAC.2011.2158172
  30. Bullo, F & Cortés, J & Martínez, S. (2009). Distributed Control of Robotics Networks. ISBN:9780691141954
  31. Souad, Marir and Faiza, Belala and Nabil, Hameurlain. Formal Modeling IoT Systems on the Basis of BiAgents and Maude, http://dx.doi.org/10.1109/ICAASE51408.2020.9380126
  32. Archibald, Blair and Shieh, Min-Zheng and Hu, Yu-Hsuan and Sevegnani, Michele and Lin, Yi-Bing, BigraphTalk: Verified Design of IoT Applications, http://dx.doi.org/10.1109/JIOT.2020.2964026
  33. Muffy Calder and Alexandros Koliousis and Michele Sevegnani and Joseph Sventek, Real-time verification of wireless home networks using bigraphs with sharing, http://dx.doi.org/10.1016/j.scico.2013.08.004
  34. Mansutti, Alessio and Miculan, Marino and Peressotti, Marco", editor="Magoutis, Kostas and Pietzuch, Peter, Multi-agent Systems Design and Prototyping with Bigraphical Reactive Systems, http://dx.doi.org/10.1007/978-3-662-43352-2_16
  35. DIB, Ahmed Taki Eddine and MAAMRI, Ramdane, Bigraphical Modelling and Design of Multi-Agent Systems, http://dx.doi.org/10.1145/3467707.3467762
  36. Pereira, Eloi and Potiron, Camille and Kirsch, Chirstoph M. and Sengupta, Raja, Modeling and controlling the structure of heterogeneous mobile robotic systems: A bigactor approach, http://dx.doi.org/10.1109/SysCon.2013.6549920