International Journal of Aeronautical and Space Sciences

The Korean Society for Aeronautical and Space Sciences (한국항공우주학회)
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Genetic Algorithm Based Decentralized Task Assignment for Multiple Unmanned Aerial Vehicles in Dynamic Environments

  • Choi, Hyun-Jin (School of Mechanical and Aerospace Engineering, Seoul National University) ;
  • Kim, You-Dan (School of Mechanical and Aerospace Engineering, Seoul National University) ;
  • Kim, Hyoun-Jin (School of Mechanical and Aerospace Engineering, Seoul National University)
  • Received : 2011.04.06
  • Accepted : 2011.06.01
  • Published : 2011.06.30
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Abstract

Task assignments of multiple unmanned aerial vehicles (UAVs) are examined. The phrase "task assignment" comprises the decision making procedures of a UAV group. In this study, an on-line decentralized task assignment algorithm is proposed for an autonomous UAV group. The proposed method is divided into two stages: an order optimization stage and a communications and negotiation stage. A genetic algorithm and negotiation strategy based on one-to-one communication is adopted for each stage. Through the proposed algorithm, decentralized task assignments can be applied to dynamic environments in which sensing range and communication are limited. The performance of the proposed algorithm is verified by performing numerical simulations.

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References

  1. Alighanbari, M. and How, J. P. (2005). Decentralized task assignment for unmanned aerial vehicles. 44th IEEE Conference on Decision and Control and the European Control Conference, Seville, Spain. pp. 5668-5673. https://doi.org/10.1109/CDC.2005.1583066
  2. Chandler, P. R., Pachter, M., Rasmussen, S., and Schumacher, C. (2002). Multiple task assignment for a UAV team. Proceedings of the AIAA Guidance, Navigation, and Control Conference and Exhibit, Monterey, CA.
  3. Choset, H. M. (2005). Principles of Robot Motion: Theory, Algorithms, and Implementation. Cambridge, MA: MIT Press.
  4. Cruz, J. B., Chen, G., Li, D., and Wang, X. (2004). Particle swarm optimization for resource allocation in UAV cooperative control. Proceedings of the AIAA Guidance, Navigation, and Control Conference and Exhibit, Rhode Island.
  5. Eun, Y. and Bang, H. (2009). Cooperative task assignment/ path planning of multiple unmanned aerial vehicles using genetic algorithms. Journal of Aircraft, 46, 338-343. https://doi.org/10.2514/1.38510
  6. Murray, R. M. (2007). Recent research in cooperative control of multivehicle systems. Journal of Dynamic Systems, Measurement, and Control, 129, 571-583. https://doi.org/10.1115/1.2766721
  7. Papadimitriou, C. H. and Steiglitz, K. (1982). Combinatorial Optimization: Algorithms and Complexity. Englewood Cliffs, NJ: Prentice Hall.
  8. Potvin, J.-Y. (1996). Genetic algorithms for the traveling salesman problem. Annals of Operations Research, 63, 337- 370. https://doi.org/10.1007/BF02125403
  9. Richards, A., Bellingham, J., Tillerson, M., and How, J. (2002). Coordination and control of multiple UAVs. Proceedings of the AIAA Guidance, Navigation, and Control Conference and Exhibit, Monterey, CA.
  10. Schumacher, C., Chandler, P., Pachter, M., and Pachter, L. (2004). Constrained optimization for UAV task assignment. Proceedings of the AIAA Guidance, Navigation, and Control Conference and Exhibit, Rhode Island.
  11. Shima, T., Rasmussen, S. J., Sparks, A. G., and Passino, K. M. (2006). Multiple task assignments for cooperating uninhabited aerial vehicles using genetic algorithms. Computers & Operations Research, 33, 3252-3269. https://doi.org/10.1016/j.cor.2005.02.039
  12. Sujit, P., Sinha, A., and Ghose, D. (2007). Team, game, and negotiation based intelligent autonomous UAV task allocation for wide area applications. In J. Chahl, L. Jain, A. Mizutani, and M. Sato-Ilic, eds. Innovations in Intelligent Machines 1 Studies in Computational Intelligence Vol 70. Heidelberg: Springer Berlin. pp. 39-75.

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