Journal of Computer Applications (计算机应用) 2013/33:12 PP.3596-3599
Due to the complex constraints, many uncertain factors and critical real-time demand of path planning for multiple Unmanned Combat Aerial Vehicle (multi-UCAV), an Improved Artificial Bee Colony (I-ABC) algorithm was proposed to solve the model of path planning for multi-UCAV. First, the Voronoi diagram of battle field space was conceived to generate the optimal area of UCAVs paths. Then the chaotic searching algorithm was used to initialize the collection of paths, which was regarded as foods of ABC algorithm. With the limited data, the initial collection could search the optimal area of paths perfectly. Finally simulations of the multi-UCAV path planning under various threats were carried out. The simulation results verify that I-ABC can improve the diversity of nectar source and the convergence rate of algorithm, and it can increase the adaptability of dynamic battlefield and unexpected threats for UCAV.