Collaborative Task Allocation for Multi-UAV Based on Genetic Algorithm

The cooperation of multiple UVAs can break through the limitation of single individual ability and improve the efficiency of mission execution. When executing large-scale tasks, the UAVs communication features, task time window and resource requirements all pose significant challenges to the collaborative task allocation algorithm. To effectively tackle the above problem, an optimization model of cooperative task allocation of heterogeneous UAVs with multiple constraints is established to meet the goal of minimizing task execution time while completing all tasks. On the basis, considering the complexity and scale-sensitivity of cooperative task allocation problem, an improved genetic algorithm is devised to solve the above model. The matrix encoded chromosome designed in our algorithm can naturally represent the resource consumption and task execution status of UAVs. Equipped with problem-specific operators, the proposed algorithm could achieve a good trade-off between the population diversity and convergence. The sufficient experimental data verify that the marked performance of our algorithm.