Mathematical Problems in Engineering Improved CNP-Method-Based Local Real-Time Cooperative Task Allocation of Heterogeneous Multi-UAV in Communication-Constrained Environment

UAVs are widely employed in military and civilian fields because of their inherent advantages. The cooperative task allocation of multi-UAV is more in conformity with the requirements of UAV application scenarios, which has become a hot research topic. However, resource consumption allocation and the application scenarios of communication constraints are often ignored. This paper proposes a distributed multi-UAV task allocation method based on improved CNP to solve the local cooperative task allocation problem of heterogeneous multi-UAV in the communication-constrained environment. The improved CNP-based method can be divided into four stages: task release, bid application, coalition formation, and signing contracts. In the task release stage, we proposed the adaptive maximum number setting method of information transfer times and the information consistency method to solve conflicts in the local communication network. In the process of coalition formation, the resource consumption allocation algorithm based on the Gini coefficient is proposed to keep the resource difference between UAVs in the coalition within a reasonable range. The simulation results demonstrate that improved CNP-method-based cooperative task allocation can handle the local real-time task allocation problem of heterogeneous multi-UAV under communication constraints; it obtains greater task rewards and spends less time on task completion than the resource-welfare-based method, PTCFA. Simultaneously, the resource consumption algorithm makes the UAV swarm maintain a more reasonable resource difference to maximize the number of missions completed.