Abstract
We present two swarm intelligence control mechanisms used for distributed robot path formation. In the first, the robots form linear chains. We study three variants of robot chains, which vary in the degree of motion allowed to the chain structure. The second mechanism is called vectorfield. In this case, the robots form a pattern that globally indicates the direction towards a goal or home location.
We test each controller on a task that consists in forming a path between two objects which an individual robot cannot perceive simultaneously. Our simulation experiments show promising results. All the controllers are able to form paths in complex obstacle environments and exhibit very good scalability, robustness, and fault tolerance characteristics. Additionally, we observe that chains perform better for small robot group sizes, while vectorfield performs better for large groups.
Article PDF
Similar content being viewed by others
Explore related subjects
Discover the latest articles, news and stories from top researchers in related subjects.Avoid common mistakes on your manuscript.
References
Arkin, R. C. (1998). Behavior-based robotics. Cambridge: MIT Press.
Batalin, M., & Sukhatme, G. S. (2002). Spreading out: a local approach to multi-robot coverage. In Proceedings of the sixth international symposium on distributed autonomous robotic systems (pp. 373–382). Berlin: Springer.
Becker, R. A., Chambers, J. M., & Wilks, A. R. (1988). The new S language. A programming environment for data analysis and graphics. London: Chapman and Hall.
Bellman, R. E. (1957). Dynamic programming. Princeton: Princeton University Press.
Birattari, M. (2005). The problem of tuning metaheuristics as seen from a machine learning perspective. DISKI (Vol. 292). Berlin: AKA/IOS Press.
Birattari, M., Stützle, T., Paquete, L., & Varrentrapp, K. (2002). A racing algorithm for configuring metaheuristics. In W. B. Langdon et al. (Eds.), Proceedings of the genetic and evolutionary computation conference (pp. 11–18). San Francisco: Morgan Kaufmann.
Campo, A., Nouyan, S., Birattari, M., Groß, R., & Dorigo, M. (2006). Negotiation of goal direction for cooperative transport. In M. Dorigo et al. (Eds.), LNCS: Vol. 4150. Ant colony optimization and swarm intelligence: 5th international workshop, ANTS 2006 (pp. 191–202). Berlin: Springer.
Christensen, A. L. (2005). Efficient neuro-evolution of hole-avoidance and phototaxis for a swarm-bot (Technical Report TR/IRIDIA/2005-14). Université Libre de Bruxelles, Belgium, DEA Thesis.
Christensen, A. L., & Dorigo, M. (2006). Evolving an integrated phototaxis and hole-avoidance behavior for a swarm-bot. In Artificial life X: proceedings of the tenth international conference on the simulation and synthesis of living systems (pp. 248–254). Cambridge: MIT Press.
Christensen, A. L., O’Grady, R., & Dorigo, M. (2007, in press). Morphology control in a self-assembling multi-robot system. IEEE Robotics & Automation Magazine.
Christensen, A. L., O’Grady, R., Birattari, M., & Dorigo, M. (2008, in press). Fault detection in autonomous robots based on fault injection and learning. Autonomous Robots.
Cohen, W. W. (1996). Adaptive mapping and navigation by teams of simple robots. Robotics and Autonomous Systems, 18, 411–434.
Deneubourg, J.-L., Aron, S., Goss, S., & Pasteels, J.-M. (1990). The self-organizing exploratory pattern of the Argentine ant. Journal of Insect Behavior, 3, 159–168.
Drogoul, A., & Ferber, J. (1992). From Tom Thumb to the dockers: some experiments with foraging robots. In From animals to animats 2. Proc. of the 2nd int. conf. on simulation of adaptive behavior (SAB92) (pp. 451–459). Cambridge: MIT Press.
Filliat, D., & Meyer, J.-A. (2003). Map-based navigation in mobile robots—I. A review of localization strategies. Cognitive Systems Research, 4, 243–282.
Goss, S., & Deneubourg, J.-L. (1992). Harvesting by a group of robots. In Proc. of the 1st European conf. on artificial life (pp. 195–204). Cambridge: MIT Press.
Howard, A. (2004). Multi-robot mapping using manifold representations. In Proc. of the 2004 IEEE int. conf. on robotics and automation (pp. 4198–4203). Los Alamitos: IEEE Computer Society.
Jakobi, N. (1997). Evolutionary robotics and the radical envelope of noise hypothesis. Adaptive Behavior, 6, 325–368.
Jakobi, N., Husbands, P., & Harvey, I. (1995). Noise and the reality gap: The use of simulation in evolutionary robotics. In F. Morán, A. Moreno, J. J. Merelo, & P. Chacón (Eds.), Lecture notes in artificial intelligence: Vol. 929. Advances in artificial life. Proceedings of the 3rd European conference on artificial life (ECAL 1995) (pp. 704–720). Berlin: Springer.
Li, Q., De Rosa, M., & Rus, D. (2003). Distributed algorithms for guiding navigation across a sensor network. In 9th international conference on mobile computing and networking (pp. 313–325). New York: ACM.
Mamei, M., & Zambonelli, F. (2005). Physical deployment of digital pheromones through RFID technology. In Proc. of the 4th int. conf. on autonomous agents and multi-agent systems, AAMAS 2005 (pp. 1353–1360). IEEE Press: Piscataway.
Meyer, J.-A., & Filliat, D. (2003). Map-based navigation in mobile robots—II. A review of map-learning and path-planning strategies. Cognitive Systems Research, 4, 283–317.
Miglino, O., Lund, H. H., & Nolfi, S. (1995). Evolving mobile robots in simulated and real environments. Artificial Life, 4, 417–434.
Mondada, F., Gambardella, L. M., Floreano, D., Nolfi, S., Deneubourg, J.-L., & Dorigo, M. (2005). The cooperation of swarm-bots: Physical interactions in collective robotics. IEEE Robotics & Automation Magazine, 12(2), 21–28.
Nouyan, S., & Dorigo, M. (2006). Chain based path formation in swarms of robots. In M. Dorigo et al. (Eds.), LNCS: Vol. 4150. Ant colony optimization and swarm intelligence: 5th international workshop, ANTS 2006 (pp. 120–131). Berlin: Springer.
Nouyan, S., Groß, R., Bonani, M., Mondada, F., & Dorigo, M. (2006). Group transport along a robot chain in a self-organised robot colony. In Proc. of the 9th int. conf. on intelligent autonomous systems (pp. 433–442). Amsterdam: IOS Press.
O’Hara, K. J., & Balch, T. R. (2004). Pervasive sensor-less networks for cooperative multi-robot tasks. In Proceedings of the seventh international symposium on distributed autonomous robotic systems. Berlin: Springer.
Payton, D., Daily, M., Estowski, R., Howard, M., & Lee, C. (2001). Pheromone robotics. Autonomous Robots, 11, 319–324.
Payton, D., Estkowski, R., & Howard, M. (2004). Pheromone robotics and the logic of virtual pheromones. In E. Şahin et al. (Ed.), LNCS: Vol. 3342. Swarm robotics: SAB 2004 international workshop (pp. 45–57). Berlin: Springer.
Svennebring, J., & Koenig, S. (2004). Building terrain covering ant robots: a feasibility study. Autonomous Robots, 116(3), 193–221.
Werger, B., & Matarić, M. (1996). Robotic food chains: externalization of state and program for minimal-agent foraging. In From animals to animats 4. Proc. of the 4th int. conf. on simulation of adaptive behavior (SAB96) (pp. 625–634). Cambridge: MIT Press.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Nouyan, S., Campo, A. & Dorigo, M. Path formation in a robot swarm. Swarm Intell 2, 1–23 (2008). https://doi.org/10.1007/s11721-007-0009-6
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11721-007-0009-6