Abstract
In most swarm systems, agents are either aware of the position of their direct neighbors or they possess a substrate on which they can deposit information (stigmergy). However, such resources are not always obtainable in real-world applications because of hardware and environmental constraints. In this paper we study in 2D simulation the design of a swarm system which does not make use of positioning information or stigmergy.
This endeavor is motivated by an application whereby a large number of Swarming Micro Air Vehicles (SMAVs), of fixed-wing configuration, must organize autonomously to establish a wireless communication network (SMAVNET) between users located on ground. Rather than relative or absolute positioning, agents must rely only on their own heading measurements and local communication with neighbors.
Designing local interactions responsible for the emergence of the SMAVNET deployment and maintenance is a challenging task. For this reason, artificial evolution is used to automatically develop neuronal controllers for the swarm of homogenous agents. This approach has the advantage of yielding original and efficient swarming strategies. A detailed behavioral analysis is then performed on the fittest swarm to gain insight as to the behavior of the individual agents.
Similar content being viewed by others
References
Basu, P., Redi, J., & Shurbanov, V. (2004). Coordinated flocking of UAVs for improved connectivity of mobile ground nodes. In Proceedings of the IEEE military communications conference (Vol. 3, pp. 1628–1634). Piscataway: IEEE Press.
Camazine, S., Deneubourg, J. L., Franks, N. R., Sneyd, J., Theraulaz, G., & Bonabeau, E. (2001). Self-organization in biological systems. Princeton: Princeton University Press.
De Nardi, R., & Holland, O. (2007). UltraSwarm: a further step towards a flock of miniature helicopters. In Lecture notes in computer science : Vol. 4433. Swarm robotics (pp. 116–128). Berlin: Springer.
Elston, J., & Frew, E. W. (2008). Hierarchical distributed control for search and tracking by heterogeneous aerial robot networks. In Proceedings of the IEEE international conference on robotics and automation (pp. 170–175). Piscataway: IEEE Press.
Flint, M., Polycarpou, M., & Fernández-Gaucherand, E. (2002). Cooperative control for multiple autonomous UAVs searching for targets. In Proceedings of the 41st IEEE conference on decision and control (Vol. 3, pp. 2823–2828). Piscataway: IEEE Press.
Gaudiano, P., Bonabeau, E., & Shargel, B. (2005). Evolving behaviors for a swarm of unmanned air vehicles. In Proceedings of the IEEE swarm intelligence symposium (pp. 317–324). Piscataway: IEEE Press.
Holland, O., Woods, J., De Nardi, R., & Clark, A. (2005). Beyond swarm intelligence: the UltraSwarm. In Proceedings of the IEEE swarm intelligence symposium (pp. 217–224). Piscataway: IEEE Press.
Hu, L., & Evans, D. (2004). Localization for mobile sensor networks. In Proceedings of the 10th annual international conference on mobile computing and networking (pp. 45–57). New York: ACM Press.
Kadrovach, B. A., & Lamont, G. B. (2001). Design and analysis of swarm-based sensor systems. In Proceedings of the 44th IEEE Midwest symposium on circuits and systems (Vol. 1, pp. 487–490). Piscataway: IEEE Press.
Kuiper, E., & Nadjm-Tehrani, S. (2006). Mobility models for UAV group reconnaissance applications. In Proceedings of the IEEE international conference on wireless and mobile communications. Piscataway: IEEE Press. doi:10.1109/ICWMC.2006.63.
Lawrence, D., Donahue, R., Mohseni, K., & Han, R. (2004). Information energy for sensor-reactive UAV flock control. In Proceedings of the AIAA 3rd “Unmanned unlimited” technical conference, AIAA paper 2004-6530. Reston: AIAA Press.
Leven, S., Zufferey, J. C., & Floreano, D. (2007). A simple and robust fixed-wing platform for outdoor flying robot experiments. In Flying insects and robots symposium (p. 69).
Lin, K., Huang, K., Li, G., & Qui, X. G. (2004). Control of swarming UAVs in collaborative missions. In TSI press series : Vol. 17. Proceedings of the World automation congress (pp. 25–30). Albuquerque: TSI Press.
McGill, R., Tukey, J. W., & Larsen, W. A. (1978). Variations of box plots. The American Statistician, 32(1), 12–116.
Merino, L., Caballero, F., Martínez-de Dios, J. R., Ferruz, J., & Ollero, A. (2006). A cooperative perception system for multiple UAVs: application to automatic detection of forest fires. Journal of Field Robotics, 23, 165–184.
Nembrini, J., Winfield, A., & Melhuish, C. (2002). Minimalist coherent swarming of wireless networked autonomous mobile robots. In From animals to animats 7, proceedings of the 7th international conference on simulation of adaptive behavior (pp. 273–382). Cambridge: MIT Press.
Nolfi, S., & Floreano, D. (2000). Evolutionary robotics: the biology, intelligence, and technology of self-organizing machines. Cambridge: MIT Press.
Oh, E. S. (2003). Information and communication technology in the service of disaster mitigation and humanitarian relief. In Proceedings of the IEEE 9th Asia-Pacific conference on communications (Vol. 2, pp. 730–734). Piscataway: IEEE Press.
Pack, D. J., & York, G. W. P. (2005). Developing a control architecture for multiple unmanned aerial vehicles to search and localize RF time-varying mobile targets: part I. In Proceedings of the IEEE international conference on robotics and automation (pp. 3954–3959). Piscataway: IEEE Press.
Parunak, H. V. D., Brueckner, S. A., & Sauter, J. (2005). Digital pheromones for coordination of unmanned vehicles. In Lecture notes in computer science : Vol. 3374. Environments for multi-agent systems (pp. 246–263). Berlin: Springer.
Reynolds, C. W. (1987). Flocks, herds and schools: a distributed behavioral model. In SIGGRAPH computer graphics (Vol. 21, pp. 25–34). New York: ACM Press.
Richards, M. D., Whitley, D., & Beveridge, J. R. (2005). Evolving cooperative strategies for UAV teams. In Proceedings of the genetic and evolutionary computation conference (Vol. 2, pp. 1721–1728). New York: ACM Press.
Rodriguez, A., Andersen, E., Bradley, J., & Taylor, C. (2007). Wind estimation using an optical flow sensor on a miniature air vehicle. In Proceedings of the AIAA conference on guidance, navigation, and control, AIAA paper 2007-6614. Reston: AIAA Press.
Şahin, E. (2005). Swarm robotics: from sources of inspiration to domains of application. In Lecture notes in computer science : Vol. 3342. Swarm robotics (pp. 10–20). Berlin: Springer.
Sauter, J. A., Matthews, R., Parunak, H. V. D., & Brueckner, S. A. (2005). Performance of digital pheromones for swarming vehicle control. In Proceedings of the 4th international joint conference on autonomous agents and multi-agent systems (pp. 903–910). New York: ACM Press.
Siegwart, R., & Nourbakhsh, I. R. (2004). Introduction to autonomous mobile robots. MIT Press, Cambridge: Bradford Book.
Soto, J., & Lin, K. C. (2005). Using genetic algorithms to evolve the control rules of a swarm of UAVs. In Proceedings of the IEEE international symposium on collaborative technologies and systems (pp. 359–365). Piscataway: IEEE Press.
Spears, W. M., Spears, D. F., Heil, R., Kerr, W., & Hettiarachchi, S. (2005). An overview of physicomimetics. In Lecture notes in computer science : Vol. 3342. Simulation of adaptive behaviour, workshop on swarm robotics (pp. 84–97). Berlin: Springer.
Støy, K. (2001). Using situated communication in distributed autonomous mobile robots. In Proceedings of the 7th Scandinavian conference on artificial intelligence (pp. 44–52). Amsterdam: IOS Press.
Vincent, P., & Rubin, I. (2004). A framework and analysis for cooperative search using UAV swarms. In Proceedings of the ACM symposium on applied computing (pp. 79–86). New York: ACM Press.
Winfield, A. (2000). Distributed sensing and data collection via broken ad hoc wireless connected networks of mobile robots. In Proceedings of distributed autonomous systems 4 (pp. 273–282). Berlin: Springer.
Winfield, A. F. T., Harper, C. J., & Nembrini, J. (2005a). Towards dependable swarms and a new discipline of swarm engineering. In Lecture notes in computer science : Vol. 4433. Swarm robotics (pp. 126–142). Berlin: Springer.
Winfield, A. F. T., Sa, J., Fernández-Gago, M. C., Dixon, C., & Fisher, M. (2005b). On formal specification of emergent behaviours in swarm robotic systems. International Journal of Advanced Robotic Systems, 2(4), 363–370.
Wu, A. S., Schultz, A. C., & Agah, A. (1999). Evolving control for distributed micro air vehicles. In Proceedings of the IEEE international symposium on computational intelligence in robotics and automation (pp. 174–179). Piscataway: IEEE Press.
Yang, Y., Minai, A. A., & Polycarpou, M. M. (2005). Evidential map-building approaches for multi-UAV cooperative search. In Proceedings of the IEEE American control conference (pp. 116–121). Piscataway: IEEE Press.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Hauert, S., Zufferey, JC. & Floreano, D. Evolved swarming without positioning information: an application in aerial communication relay. Auton Robot 26, 21–32 (2009). https://doi.org/10.1007/s10514-008-9104-9
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10514-008-9104-9