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Cooperative task assignment of multiple heterogeneous unmanned aerial vehicles using a modifed genetic algorithm with multi-type genes

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Chinese Journal of Aeronautics 2013年第5期26卷 1238-1250页

作者： Deng Qibo Yu Jianqiao Wang Ningfei Key Laboratory of Dynamics and Control of Flight Vehicle Ministry of EducationSchool of Aerospace EngineeringBeijing Institute of Technology

The task assignment problem of multiple heterogeneous unmanned aerial vehicles （UAVs）, concerned with cooperative decision making and control, is studied in this paper. The heterogeneous vehicles have different operational capabilities and kinematic constraints, and carry limited resources （e.g., weapons） onboard. They are designated to perform multiple consecutive tasks cooperatively on multiple ground targets. The problem becomes much more complicated because of these terms of heterogeneity. In order to tackle the challenge, we modify the former genetic algorithm with multi-type genes to stochastically search a best solution. Genes of chromo- somes are different, and they are assorted into several types according to the tasks that must be performed on targets. Different types of genes are processed specifically in the improved genetic operators including initialization, crossover, and mutation. We also present a mirror representation of vehicles to deal with the limited resource constraint. Feasible chromosomes that vehicles could perform tasks using their limited resources under the assignment are created and evolved by genetic operators. The effect of the proposed algorithm is demonstrated in numerical simulations. The results show that it effectively provides good feasible solutions and finds an optimal one.

关键词： Cooperative control Genetic algorithm heterogeneous unmanned aerial vehicles Multi-type genes Task assignment

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