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| Path Planning for UCAV Based on Voronoi Diagram and Quantum-Behaved Particle Swarm Algorism |
| ZHAO Yanli1, ZHAO Xiaohu2, LIU Kangming3 |
| 1. College of Computer and Information Technology, Nanyang Normal University, Nanyang 473061, Henan Province, China;2. China Academy of Electronics and Infomation Technology, China Electronics Technology Group Corporation, Beijing 100041, China;3. College of Information Engineering, Huanghuai University, Zhumadian 463000, Henan Province, China |
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Abstract: Path routing for Unmanned Combat Aerial Vehicle (UCAV) can be defined as the task of Unmanned Combat Aerial Vehicle automatically executing, which is a complex optimization problem. It is very hard to get the optimal solution in polynomial time. Therefore, in this paper a path planning method was proposed based on Voronoi diagram and Quantum-behaved Particle Swarm Optimization (QPSO) algorism. Firstly, the cost model for path planning of UCAV was defined by totally consideration for the radar threat and fuel consumption, and the Voronoi diagram was generated according to the given threat source. And then the initial path planning set was constructed by initial sites, the vertex of Voronoi diagram and the final sites. Finally, in order to conquer the problem of PSO algorism that has the defects of falling to optimal location, the Cauchy mutation random number was introduced to improve the global search ability of QPSO algorism, and using the improved QPSO algorism to plan path the specific algorism was defined. The result of simulation experiment shows the method proposed in this paper can obtain the optimal solution for UCAV, and it has the optimal cost 280 in comparison with PSO 600 and QPSO 350, respectively. Meanwhile, at the mean time, when the iteration time is 250, the improved QPSO in our paper is in convergence, so it can provide not only the optimal solution but also the rapid convergence speed. Thus it has big superiority over the other methods.
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Received: 13 March 2013
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2013, Vol. 31 
