Aiming at the path planning for the Unmanned Aerial Vehicles (UAVs) in flight mission, a novel improved Artificial Bee Colony (ABC) algorithm is presented and used in flight mission.The path planning problem is transformed into function optimization based on this algorithm.The algorithm can evolve toward a better direction with the information exchanges among the colony and mechanism for the survival of the fittest.In the stage of employed bee search, an adaptive search strategy is adopted to increase the speed of convergence.In the stage of following bee search, a new probability of selection strategy is introduced to keep the diversity of the population.And in the stage of scout bee search, the chaotic search operator is used to improve the ability of global search.Through the standard function tests and simulation of path planning, the superiority of the improved algorithm is proved.All the results show that the proposed algorithm can improve the global optimizing ability, has great advantages on convergence speed and robustness over the traditional ABC algorithm, and is fit for UAV path planning.