Jesus Manuel de la Cruz
Luis Torre-Cubillo
ABSTRACT
This paper presents a path planner for Unmanned Air Vehicles (UAVs) based on Evolutionary Algorithms (EA) that can be used in realistic risky scenarios. The path returned by the algorithm fulfills and optimizes multiple criteria which (1) are calculated based on properties of real UAVs, terrains, radars and missiles, and (2) are used to rank the solutions according to the priority levels and goals selected for each mission. Developed originally to work with only one UAV, the planner currently allows us to obtain the optimal path of several UAVs that are flying simultaneously. It works globally offline and locally online to recalculate a part of the path when an unexpected threat appears. Finally, the effectiveness of the solutions given by this planner has been successfully tested against a simulator that implements a complex model of the UAV and its environment.
- Andres-Toro, B., Besada-Portas, E., Fernandez-Blanco, P., Lopez Orozco, J.A., and de la Cruz, J.M. 2002. Multiobjective optimization of dynamic processes by evolutionary algorithms. In Proceeding of the 15th Triennial World Congress of the IFAC. (Barcelona, Spain, July 2002)Google Scholar
- Besada-Portas, E., Lopez-Orozco, J.A., Andres-Toro, B. 2002. A versatile toolbox for solving industrial problems with several evolutionary techniques. Evolutionary methods for Design, Optimization and Control. International Center for Numerical Methods in Engineering. March 2002.Google Scholar
- Coello Coello, C.A., and Salazar Lechuga, M. 2002. MOPSO: A proposal for multiple objective particle swarm optimization. In Proceeding of Congress on Evolutionary Computation (CEC'2002). (Piscataway, New Jersey, May 2002). Google ScholarDigital Library
- Farin, G. 1988. Curves and Surfaces for Computer Aided Geometric Design. A practical Guide. New York:Academic. Google ScholarDigital Library
- Fonseca, C.M., Fleming, P.J. 1998. Multiobjective Optimization and Multiple Constraint Handling with Evolutionary Algorithms- Part I: Unificied Formulation. Transactions on Systems, Man and Cybernetics. Part A: Systems and Humans. Vol 28, no. 1, (January 1998). 26--37. Google ScholarDigital Library
- Kuwata,Y. and How J. 2004. Three Dimensional Receding Horizon Control for UAVs. In Proceedings of AIAA Guidance, Navigation, and Control Conference and Exhibit, (August 2004). AIAA 2004--5144.Google Scholar
- Mittal, S., and Deb, K. 2004. Three-Dimensional Offline Path Planning for UAVs Using Multiobjective Evolutionary Algorithms. Kangal Report no. 2004-008Google Scholar
- Nikolos, I.K., Valavanis, K.P., Tsourveloudis, N.C. and Kostaras, A.N. 2003. Evolutionary Algorithm Based Offline/Online Path Planner for UAV Navigation, IEEE Transactions on Systems, Man, and Cybernetics - Part B: Cybernetics, Vol 33, no. 6 (December 2003). Google ScholarDigital Library
- Raghunathan, A., Gopal, V., Subramanian, D., Biegler, L. and Samad, T. 2004. Dynamic Optimization Strategies for 3D Conflict Resolution of Multiple Aircraft. AIAA Journal of Guidance, Control and Dynamics, 27 (4). (2004), 586--594.Google Scholar
- Richards, A.G., How, J.P. 2002. Aircraft Trajectory Planning with Collision Avoidance Using Mixed-Integer Linear Programming. In Proceeding of the American Control Conference (May 2002).Google ScholarCross Ref
- Ruz, J.J., Arévalo, O., de la Cruz, J.M, and Pajares, G. 2006. Using MILP for UAVs Trajectory Optimization under Radar Detection Risk. In Proceedings of the 11th IEEE International Conference on Emerging Technologies and Factory Automation (Prague, September 2006).Google Scholar
- Shima, T., Schumachery, C. 2005. Assignment of Cooperating UAVs to Simultaneous Tasks using Genetic Algorithms. In Proceeding of the AIAA Guidance, Navigation, and Control Conference and Exhibit. 15--18 (San Francisco, California, August 2005).Google Scholar
- Stevens, B., Lewis F. 2004. Aircraft Control and Simulation. 2nd Edition. Wiley. 2004.Google Scholar
- Szczerba, R.J. 1999. Thread netting for real-time, intelligent route planners. In Proceeding of the IEEE Symp. Inf., Decision and Control. (Adelaida, Autralia, 1999)Google Scholar
- Szczerba, R.J., Galkowski, P., Glicktein, I.S., Ternullo, N. 2000. Robust algorithm for real-time route planning. IEEE Transactions on Aerospace and Electronic Systems, vol. 36, 3, (July 2000), 869--878.Google ScholarCross Ref
- Tian, J., Shen, L., Zheng, Y. 2006. Genetic Algorithm Based Approach for Multi-UAV Cooperative Reconnaissance Mission Planning Problem. Lectures notes in Computer Science. Springer Berlin. Volume 4203/2006. Google ScholarDigital Library
- Trovato, K.I. 1996. A* Planning in Discrete Configuration Spaces of Autonomous Systems. PhD thesis, Amsterdam University, 1996.Google Scholar
- Veldhuizen, D. A. V. and G. B. Lamont.1998. Evolutionary computation and convergence to a pareto front. In Proceeding of the Genetic Programming 1998 Conference.Google Scholar
- Zheng, C., Li, L., Xu, F., Sun F., and Ding, M., Evolutionary Route Planner for Unmanned Air Vehicles, IEEE Transaction on Robotics, Vol. 21, no. 4, (August 2005), 609--620 Google ScholarDigital Library
Index Terms
- Evolutionary path planner for UAVs in realistic environments
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