Abstract
Recent years have witnessed a rapidly growing interest in using teams of mobile robots for autonomously covering environments. In this paper a novel approach for multi-robot coverage is described which is based on the principle of pheromone-based communication. According to this approach, called StiCo (for “Stigmergic Coverage”), the robots communicate indirectly via depositing/detecting markers in the environment to be covered. Although the movement policies of each robot are very simple, complex and efficient coverage behavior is achieved at the team level. StiCo shows several desirable features such as robustness, scalability and functional extensibility. Two extensions are described, including A-StiCo for dealing with dynamic environments and ID-StiCo for handling intruder detection. These features make StiCo an interesting alternative to graph-based multi-robot coverage approaches which currently are dominant in the field. Moreover, because of these features StiCo has a broad application potential. Simulation results are shown which clearly demonstrate the strong coverage abilities of StiCo in different environmental settings.
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References
Roman-Ballesteros, I., Pfeiffer, C.F.: A framework for cooperative multi-robot surveillance tasks. In: Electronics, Robotics and Automotive Mechanics Conference, vol. 2, pp. 163 –170 (September 2006)
Schwager, M., Rus, D., Slotine, J.J.: Decentralized, adaptive coverage control for networked robots. International Journal of Robotics Research 28(3), 357–375 (2009)
Cortes, J., Martinez, S., Karatas, T., Bullo, F.: Coverage control for mobile sensing networks. IEEE Transactions on Robotics and Automation 20(2), 243–255 (2004)
Ranjbar-Sahraei, B., Weiss, G., Nakisaee, A.: Stigmergic coverage algorithm for multi-robot systems (demonstration). In: Proceedings of the Eleventh International Conference on Autonomous Agents and Multiagent Systems, AAMAS (2012)
Dorigo, M.: Optimization, Learning and Natural Algorithms. Thesis report, Politecnico di Milano, Italy (1992)
Dorigo, M., Birattari, M., Stutzle, T.: Ant colony optimization. IEEE Computational Intelligence Magazine 1(4), 28–39 (2006)
Johansson, R., Saffiotti, A.: Navigating by stigmergy: A realization on an rfid floor for minimalistic robots. In: IEEE International Conference on Robotics and Automation, ICRA 2009, pp. 245–252 (May 2009)
Herianto, Sakakibara, T., Kurabayashi, D.: Artificial pheromone system using rifd for navigation of autonomous robots. Journal of Bionic Engineering 4(4), 245–253 (2007)
Wagner, I.A., Lindenbaum, M., Bruckstein, A.M.: Distributed covering by ant-robots using evaporating traces. IEEE Transactions on Robotics and Automation 15(5), 918–933 (1999)
Elor, Y., Bruckstein, A.M.: Autonomous Multi-agent Cycle Based Patrolling. In: Dorigo, M., Birattari, M., Di Caro, G.A., Doursat, R., Engelbrecht, A.P., Floreano, D., Gambardella, L.M., Groß, R., Şahin, E., Sayama, H., Stützle, T. (eds.) ANTS 2010. LNCS, vol. 6234, pp. 119–130. Springer, Heidelberg (2010)
Elor, Y., Bruckstein, A.M.: Multi-a(ge)nt graph patrolling and partitioning. In: Proceedings of the 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology - Volume 02, WI-IAT 2009, pp. 52–57. IEEE Computer Society, Washington, DC (2009)
Glad, A., Simonin, O., Buffet, O., Charpillet, F.: Influence of different execution models on patrolling ant behaviors: from agents to robots. In: Proceedings of the Ninth International Conference on Autonomous Agents and MultiAgent Systems, AAMAS 2010 (2010)
Glad, A., Simonin, O., Buffet, O., Charpillet, F.: Theoretical study of ant-based algorithms for multi-agent patrolling. In: Proceeding of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence, pp. 626–630. IOS Press, Amsterdam (2008)
Yanovski, V., Wagner, I.A., Bruckstein, A.M.: A distributed ant algorithm for efficiently patrolling a network. Algorithmica 37, 165–186 (2003)
Cortes, J., Martinez, S., Bullo, F.: Spatially-distributed coverage optimization and control with limited-range interactions. ESAIM: Control, Optimisation and Calculus of Variations 11, 691–719 (2005)
Schwager, M., Rus, D., Slotine, J.J.: Unifying geometric, probabilistic, and potential field approaches to multi-robot deployment. International Journal of Robotics Research 30(3), 371–383 (2011)
Breitenmoser, A., Schwager, M., Metzger, J.C., Siegwart, R., Rus, D.: Voronoi coverage of non-convex environments with a group of networked robots. In: Proc. of the International Conference on Robotics and Automation (ICRA 2010), pp. 4982–4989 (May 2010)
Fujisawa, R., Imamura, H., Hashimoto, T., Matsuno, F.: Communication using pheromone field for multiple robots. In: IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2008, pp. 1391–1396 (September 2008)
Ziparo, V.A., Kleiner, A., Marchetti, L., Farinelli, A., Nardi, D.: Cooperative exploration for USAR robots with indirect communication. In: Proc.of 6th IFAC Symposium on Intelligent Autonomous Vehicles, IAV 2007 (2007)
Bullo, F., Cortes, J., Martinez, S.: Distributed Control of Robotic Networks. Applied Mathematics Series (2009), http://www.coordinationbook.info
Dubins, L.E.: On curves of minimal length with a constraint on average curvature and with prescribed initial and terminal positions and tangents. American Journal of Mathematics 79, 497–516 (1957)
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Ranjbar-Sahraei, B., Weiss, G., Nakisaee, A. (2012). A Multi-robot Coverage Approach Based on Stigmergic Communication. In: Timm, I.J., Guttmann, C. (eds) Multiagent System Technologies. MATES 2012. Lecture Notes in Computer Science(), vol 7598. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33690-4_13
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DOI: https://doi.org/10.1007/978-3-642-33690-4_13
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