Skip to main content

A Simulation Environment for Autonomous Robot Swarms with Limited Communication Skills

  • Conference paper
  • First Online:
Simulation Tools and Techniques (SIMUtools 2020)

Abstract

We present a novel real-time simulation tool for modeling and analyzing a swarm of distributed autonomous mobile robots communicating over an unreliable and capacity restricted communication network. The robots are setup as ground vehicles and use C-PBP [8] as model predictive closed loop controller. This tool offers the ability to simulate rural as well as completely urban scenarios with static obstacles, dynamic obstacles with scripted movement, soil condition, noise floor, active jammers and static and dynamic obstacles for the links with adjustable damping. The goal of this simulation is the analysis of swarm behavior of robots for given missions such as terrain exploration, convoy escorting or creation of a mobile ad hoc network in disaster areas under realistic environmental conditions.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 149.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 199.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Ahlers, E.: Funk-übersicht: WLAN-Wissen für Gerätewahl und Fehlerbeseitigung. c’t 2015(15), 178–181 (2015). https://www.heise.de/ct/ausgabe/2015-15-WLAN-Wissen-fuer-Geraetewahl-und-Fehlerbeseitigung-2717917.html

  2. Baumann, D., Mager, F., Zimmerling, M., Trimpe, S.: Control-guided communication: efficient resource arbitration and allocation in multi-hop wireless control systems. IEEE Control Syst. Lett. 4(1), 127–132 (2020)

    Article  MathSciNet  Google Scholar 

  3. Euler, J.: Optimal cooperative control of UAVs for dynamic data-driven monitoring tasks. Dissertation, Technische Universität Darmstadt, Darmstadt (2018)

    Google Scholar 

  4. Euler, J., von Stryk, O.: Optimized vehicle-specific trajectories for cooperative process estimation by sensor-equipped UAVs. In: 2017 IEEE International Conference on Robotics and Automation, ICRA 2017, Singapore, Singapore, 29 May–3 June 2017, pp. 3397–3403. IEEE (2017)

    Google Scholar 

  5. Friis, H.T.: A note on a simple transmission formula. Proc. IRE 34(5), 254–256 (1946)

    Article  Google Scholar 

  6. Fukushima, H., Kon, K., Matsuno, F.: Distributed model predictive control for multi-vehicle formation with collision avoidance constraints. In: Proceedings of the 44th IEEE Conference on Decision and Control, pp. 5480–5485. IEEE (2005)

    Google Scholar 

  7. Grüne, L., Pannek, J.: Nonlinear Model Predictive Control: Theory and Algorithms. CCE. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-46024-6

    Book  MATH  Google Scholar 

  8. Hämäläinen, P., Rajamäki, J., Liu, C.K.: Online control of simulated humanoids using particle belief propagation. In: Proceedings of SIGGRAPH 2015. ACM, New York (2015)

    Google Scholar 

  9. Ihler, A., McAllester, D.: Particle belief propagation. In: International Conference on Artificial Intelligence and Statistics, vol. 5, pp. 256–263 (2009)

    Google Scholar 

  10. Jacob, B.: Eigen. http://eigen.tuxfamily.org/index.php?title=Main_Page

  11. Kuntz, A., Schmidt-Eisenlohr, F., Graute, O., Hartenstein, H., Zitterbart, M.: Introducing probabilistic radio propagation models in OMNeT++ mobility framework and cross validation check with NS-2. In: Molnár, S., Heath, J.R., Dalle, O., Wainer, G.A. (eds.) Proceedings of the 1st International Conference on Simulation Tools and Techniques for Communications, Networks and Systems & Workshops, SimuTools 2008, Marseille, France, 3–7 March 2008, p. 72. ICST/ACM (2008)

    Google Scholar 

  12. Lächele, J., Franchi, A., Bülthoff, H.H., Robuffo Giordano, P.: SwarmSimX: real-time simulation environment for multi-robot systems. In: Noda, I., Ando, N., Brugali, D., Kuffner, J.J. (eds.) SIMPAR 2012. LNCS (LNAI), vol. 7628, pp. 375–387. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-34327-8_34

    Chapter  Google Scholar 

  13. Lamport, L.: Time, clocks, and the ordering of events in a distributed system. Commun. ACM 21(7), 558–565 (1978)

    Article  Google Scholar 

  14. Mager, F., Baumann, D., Jacob, R., Thiele, L., Trimpe, S., Zimmerling, M.: Feedback control goes wireless: guaranteed stability over low-power multi-hop networks. In: Liu, X., Tabuada, P., Pajic, M., Bushnell, L. (eds.) Proceedings of the 10th ACM/IEEE International Conference on Cyber-Physical Systems, ICCPS 2019, Montreal, QC, Canada, 16–18 April 2019, pp. 97–108. ACM (2019)

    Google Scholar 

  15. Puzicha, A.: Modeling and analysis of a distributed non-linear model-predictive control for swarms of autonomous robots with limited communication skills (in German). Master’s thesis, Department of Computer Science, TU Dortmund (2019)

    Google Scholar 

  16. Ritter, T.: PDE-based dynamic data-driven monitoring of atmospheric dispersion processes. Dissertation, Technische Universität Darmstadt, Darmstadt (2017)

    Google Scholar 

  17. Strobel, A.: Verteilte nichtlineare modellprädiktive Regelung von unbemannten Luftfahrzeug-Schwärmen. Dissertation, Technische Universität Darmstadt, Darmstadt (2016)

    Google Scholar 

  18. Tricaud, C., Chen, Y.: Optimal Mobile Sensing and Actuatin Policies in Cyber-physical Systems. Springer, London (2011). https://doi.org/10.1007/978-1-4471-2262-3

    Book  Google Scholar 

  19. Vieira, B., Severino, R., Filho, E.V., Koubaa, A., Tovar, E.: Copadrive - a realistic simulation framework for cooperative autonomous driving applications. In: Proc. 8th IEEE International Conference on Connected Vehicles and Expo (ICCVE 2019). IEEE (2019)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Alexander Puzicha .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2021 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Puzicha, A., Buchholz, P. (2021). A Simulation Environment for Autonomous Robot Swarms with Limited Communication Skills. In: Song, H., Jiang, D. (eds) Simulation Tools and Techniques. SIMUtools 2020. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 370. Springer, Cham. https://doi.org/10.1007/978-3-030-72795-6_17

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-72795-6_17

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-72794-9

  • Online ISBN: 978-3-030-72795-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics