Year 2019,
Volume: 2 Issue: 1, 37 - 47, 23.09.2019
Abderahmane Benkirat
Ouarda Zedadra
References
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A Multiple-Place Algorithm for Sustainable Foraging Scenarios
Year 2019,
Volume: 2 Issue: 1, 37 - 47, 23.09.2019
Abderahmane Benkirat
Ouarda Zedadra
Abstract
We proposed in this paper a Multi-Place Foraging algorithm called Lévy Walk and Firefly Recruiting Algorithm (LWFR). Unlike, most of the literature works on foraging, our foraging robots forage to maintain the survivability of their nests and collaborate to maintain the survivability of other depots when needed. The Proposed algorithm uses: (1) Lévy Walk to search objects;(2) Firefly algorithm to attract robots in neighborhood. The attraction model inspired by the behavior of Fireflies provides an indirect and costless communication. Numerical simulations show that the proposed algorithm can maintain the survivability of different nests.
References
- Ådahin, E., Girgin, S., Bayindir, L., Turgut, A.E.: Swarm Robotics. In: Swarm Intelligence, pp. 87–100. Springer Berlin Heidelberg, Berlin, Heidelberg (2008). https://doi.org/10.1007/978-3-540-74089-6-3
- Bonabeau, E., Theraulaz, G., Deneubourg, J.L.: Fixed response thresholds and the regulation of division of labor in insect societies. Bulletin of Mathematical Biology 60(4), 753–807 (1998). https://doi.org/10.1006/bulm.1998.0041
- Castello, E., Yamamoto, T., Nakamura, Y., Ishiguro, H.: Task Allocation for a robotic swarm based on an Adaptive Response Threshold Model. In: 2013 13th International Conference on Control, Automation and Systems (ICCAS 2013). pp. 259–266. No. Iccas, IEEE (oct 2013).https://doi.org/10.1109/ICCAS.2013.6703905
- Castello, E., Yamamoto, T., Nakamura, Y., Ishiguro, H.: Foraging optimization in swarm robotic systems based on an adaptive response threshold model. Advanced Robotics 28(20), 1343–1356 (oct 2014). https://doi.org/10.1080/01691864.2014.939104
- Hecker, J.P., Moses, M.E.: Beyond pheromones: evolving error-tolerant, flexible, and scalable ant-inspired robot swarms. Swarm Intelligence 9(1), 43–70 (feb 2015). https://doi.org/10.1007/s11721-015-0104-z
- Lu, Q., Hecker, J.P., Moses, M.E.: The MPFA: A multiple-place foraging algorithm for biologically-inspired robot swarms. In: 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). vol. 2016-Novem, pp. 3815–3821. IEEE (oct 2016).https://doi.org/10.1109/IROS.2016.7759561
- Lu, Q., Hecker, J.P., Moses, M.E.: Multiple-place swarm foraging with dynamic depots. Autonomous Robots 42(4), 909–926 (apr 2018). https://doi.org/10.1007/s10514-017-9693-2
- Pinciroli, C., Trianni, V., Oâ˘A ´ ZGrady, R., Pini, G., Brutschy, A., Brambilla, M., Mathews, N., Ferrante, E., Di Caro, G., Ducatelle, F., et al.: Argos: a modular, parallel, multi-engine simulator for multi-robot systems. Swarm intelligence 6(4), 271–295 (2012)
- Sahin, E.: Swarm Robotics, Lecture Notes in Computer Science, vol. 3342. Springer Berlin Heidelberg, Berlin, Heidelberg (2005). https://doi.org/10.1007/b105069
- Tisue, S., Wilensky, U.: Netlogo: Design and implementation of a multi-agent modeling environment. In: Proceedings of agent. vol. 2004, pp. 7–9 (2004)