Automated Task Allocation for Multi-Drone Reconnaissance Missions Based on Optimized Discrete Particle Swarm Optimization

With the increasing complexity of the mission environment, the cooperative execution of tasks by multiple UAVs has become an inevitable trend. This paper focuses on the automatic allocation of reconnaissance tasks for multiple UAVs and proposes an optimized discrete particle swarm algorithm. Firstly, the process of collaborative task instruction requests is optimized to reduce the response time. Then, an automated task allocation model with various constraints and performance functions is constructed. Subsequently, the model is solved based on the optimized discrete particle swarm algorithm. Through comparative experiments with other common methods, the results show that this algorithm performs well in terms of task allocation efficiency, the optimal value of the objective function, and execution time. It effectively improves the automatic task allocation ability of multiple UAVs in reconnaissance tasks and provides a strong guarantee for their cooperative operations.