This paper mainly studies the coordination task assignment problem faced by multi-UAV systems when performing area search tasks. First, for the coverage search task, by analyzing the task load of each UAV, this paper proposes and establishes a dynamic model of UAV task load based on the biological competition mechanism, and proves that the model can realize the area under the condition of weighted threat probability. Even distribution of search tasks. Secondly, on the basis of solving the priority traveling salesman problem, through simulated annealing algorithm, the established priority traveling salesman problem is solved, and the path planning method of UAV is obtained. Finally, through simulation experiments, the effectiveness and engineering practical significance of the area search task assignment method proposed in this paper are verified. 

This paper investigates the multiple unmanned aerial vehicle (multi-UAV) cooperative task assignment problem. Specifically, we assign different types of UAVs to accomplish the classification, attack, and verification tasks of targets under resource, precedence, and timing constraints. Due to complex coupling among these tasks, we decompose the considered problem into two subproblems: one with continuous and independent tasks and another with continuous and correlative tasks. To solve them, we first present an adjustable, fully adaptive cross-entropy (AFACE) algorithm based on the cross-entropy (CE) method, which serves as a stepping stone for developing other algorithms. Secondly, to overcome task precedence in the first subproblem, we propose a mutually independent AFACE (MIAFACE) algorithm, which converges faster than the CE method when obtaining the optimal scheme vectors of these continuous and independent tasks. Thirdly, to deal with task coupling in the second subproblem, we present a mutually correlative AFACE (MCAFACE) algorithm to find the optimal scheme vectors of these continuous and correlative tasks, while its computational complexity is inferior to that of the MIAFACE algorithm. Finally, numerical simulations demonstrate that the proposed MIAFACE (MCAFACE, respectively) algorithm consumes less time than the existing algorithms for the continuous and independent (correlative, respectively) task assignment problem.

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A coordinated assignment method for multi-UAV area search tasks

Citations

Adjustable Fully Adaptive Cross-Entropy Algorithms for Task Assignment of Multi-UAVs

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