【摘要】 对一类典型的多无人机协同任务进行任务规划建模,并设计了一种基于整数编码的混合遗传算法进行任务分配的方法。该方法充分利用约束提供的启发信息,从编码方式和遗传算子两个方面提高遗传个体的约束满足率,从而提高算法的求解性能。同时为了保证任务规划的准确性,在协同任务规划前进行路径预规划。为了研究算法的性能,引入一种统计学的评价准则,并基于此评价准则进行遗传算法参数的选择。算法验证表明,该方法能有效解决多无人机协同任务分配问题,且对任务规划中的多约束条件和多目标规划具有较好的鲁棒性。更多还原

【Abstract】 A cooperation task allocation model of multiple UAVs( Unmanned Aerial Vehicles) for a typical mission is formulated. A method based on hybrid genetic algorithm with integer coding for multiple UAVs’ cooperation task allocation is designed, it makes full use of heuristic information provided by constraints and increases the ratio of chromosomes which satisfi es all constraints, so as to improves the performance of the algorithm with the new coding and genetic operators. Path planning is implemented before cooperative task allocation, it makes the task allocation more accurate. In order to study the performance of algorithm, a kind of statistical evaluation criterion is introduced, based on which the parameters of genetic algorithm are selected. Simulation results indicate that, the method proposed in this paper is effective for cooperation task allocation and more robust to multiple constraints and multi objective programming.更多还原