Journal of the Korean Society for Aeronautical & Space Sciences (한국항공우주학회지)

The Korean Society for Aeronautical and Space Sciences (한국항공우주학회)
권호 표지
DOI QR코드

DOI QR Code

Task Assignment of Multiple UAVs using MILP and GA

혼합정수 선형계획법과 유전 알고리듬을 이용한 다수 무인항공기 임무할당

  • 최현진 (서울대학교 기계항공공학부 대학원) ;
  • 서중보 (서울대학교 기계항공공학부 대학원) ;
  • 김유단 (서울대학교 기계항공공학부)
  • Received : 2010.02.11
  • Accepted : 2010.04.12
  • Published : 2010.05.01
Download PDF
⟨ Previous Next ⟩

Abstract

This paper deals with a task assignment problem of multiple UAVs performing multiple tasks on multiple targets. The task assignment problem of multiple UAVs is a kind of combinatorial optimization problems such as traveling salesman problem or vehicle routing problem, and it has NP-hard computational complexity. Therefore, computation time increases as the size of considered problem increases. To solve the problem efficiently, approximation methods or heuristic methods are widely used. In this study, the problem is formulated as a mixed integer linear program, and is solved by a mixed integer linear programming and a genetic algorithm, respectively. Numerical simulations for the environment of the multiple targets, multiple tasks, and obstacles were performed to analyze the optimality and efficiency of each method.

본 논문은 다수의 목표물과 다수의 임무가 존재하는 상황에서의 다수 무인항공기의 임무할당 문제를 다룬다. 다수 무인항공기의 임무할당 문제는 순회 세일즈맨 문제, 차량 라우팅 문제와 같은 조합최적화 문제의 일종으로 NP-hard의 계산 복잡도를 가지고 있다. 이런 성격의 문제는 문제의 크기가 커질수록 계산시간이 급격히 증가하는 특징을 지니기 때문에 문제를 효율적으로 풀기 위해서 근사화 방법 또는 발견적인 방법을 사용한다. 본 연구에서는 임무할당 문제를 혼합정수 선형계획 문제로 정식화하고, 혼합정수 선형계획법과 유전 알고리듬으로 해를 구하였다. 다수의 목표물, 다수의 임무, 장애물이 존재하는 환경에 대한 수치 시뮬레이션을 수행하여 각 방법의 최적성과 효율성에 대해 검토하였다.

Keywords

References

  1. R. M. Murray, “Recent Research inCooperative Control of Multivehicle Systems”,Journal of Dynamic Systems, Measurement, andControl, Vol. 129, No. 5, 2007, pp. 571-583. https://doi.org/10.1115/1.2766721
  2. F. Giulietti, L. Pollini, and M. Innocenti,"Autonomous Formation Flight”, IEEE ControlSystems Magazine, Vol. 20, No. 6, 2000, pp34-44. https://doi.org/10.1109/37.887447
  3. C. H. Papadimitriou, and K. Steiglitz,Combinatorial Optimization: Algorithms andComplexity, Prentice-Hall, Englewood Cliffs, NJ,1982.
  4. T. H. Cormen, C. E. Leiserson, R. L.Rivest, and C. Stein, Introduction to Algorithms,2nd Ed., MIT Press, Cambridge, MA, 2001.
  5. A. Richards, J. Bellingham, M. Tillerson,and J. P. How, “Coordination and Control ofMultiple UAVs”, AIAA Guidance, Navigation, andControl Conference, Monterey, CA, Aug. 2002.
  6. C. Schumacher, P. Chandler, M. Pachter,and L. Pachter, “Constrained Optimization forUAV Task Assignment”, AIAA Guidance,Navigation, and Control Conference, Providence,RI, Aug. 2004.
  7. M. Alighanbari, Y. Kuwata, and J. P. How, "Coordination and Control of Multiple UAVs with Timing Constraints and Loitering”, American Control Conference, Denver, CO, June 2003. https://doi.org/10.1109/ACC.2003.1242572
  8. A. Salman, I. Ahmad, and S. Al-Madani “,Particle Swarm Optimization for TaskAssignment Problem”, Microprocessors andMicrosystems, Vol. 26, No. 8, 2002, pp. 363-371. https://doi.org/10.1016/S0141-9331(02)00053-4
  9. S. J. Rasmussen, and T. Shima, “Tree Search Algorithm for Assigning Cooperating UAVs to Multiple Tasks”, International Journal of Robust Nonlinear Control, Vol. 18, No. 2, 2007, pp. 135-153. https://doi.org/10.1002/rnc.1257
  10. J. Y. Protvin, “Genetic Algorithms for the Travelling Salesman Problem”, Annals of Operations Research, Vol. 63, No. 3, 1996, pp. 339-370. https://doi.org/10.1007/BF02125403
  11. T. Shima, S. J. Rasmussen, A. G. Sparks,and K. M. Passino, “Multiple TaskAssignments for Cooperating UninhabitedAerial Vehicles using Genetic Algorithms”,Computers & Operation Research, Vol. 33, No.11, 2006, pp. 3252-3269. https://doi.org/10.1016/j.cor.2005.02.039
  12. Y. Eun, and H. Bang, “Cooperative TaskAssignment/Path Planning of MultipleUnmanned Aerial Vehicles Using GeneticAlgorithms”, Journal of Aircraft, Vol. 46, No. 1,2009, pp. 338-343. https://doi.org/10.2514/1.38510
  13. H. Alt, and E. Welzl. "Visibility Graphs and Obstacle-Avoiding Shortest Paths”, Mathematical Methods of Operations Research, Vol. 32, No. 3-4, 1988, pp. 145-164. https://doi.org/10.1007/BF01928918
  14. 문병로, 쉽게 배우는 유전 알고리즘 진화적 접근법, 한빛미디어, 2008.

Cited by

  1. Combinatorial Optimization Model of Air Strike Packages based on Target Groups vol.42, pp.6, 2016, https://doi.org/10.7232/JKIIE.2016.42.6.386