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A novel approach of path planning for unmanned aerial vehicle (UAV) is presented based on immune genetic algorithm (IGA) with elitist. IGA introduces immune operator and concentration mechanism which improve the inherent defects of premature and slow convergence speed existing in genetic algorithm (GA). Simulation results show that an ideal flight path can be more quickly searched using IGA, under conditions of meeting the requirements for UAV and the given constraints. Correctness and effectiveness of IGA are verified.