Cooperative reconnaissance mission planning for heterogeneous UAVs with DCSA

Abstract

In this paper, an improved Discrete Cuckoo Search algorithm (DCSA) is proposed to solve the problem of cooperative reconnaissance mission planning for multi-heterogeneous UAVs, to maximize the reconnaissance revenue of UAVs and achieve the shortest total mission time in the combat areas. DCSA achieves the balance between local and global solutions via Lévy flights in the search space. At the same time, it avoids falling into local optimal solution. Considering the heterogeneity and resource constraints of UAVs, the multi-heterogeneous UAVs cooperative reconnaissance task planning model has been established, which is based on the evaluation criteria of total investigative revenue and the longest time consumption of UAV. Meanwhile, the UAV-task combination sequence is constructed. Therefore, the task planning problem is transformed into Traveling Salesman Problem (TSP). With the aid of DCSA, the task planning problem is simplified effectively. As the result in simulation shows, the improved DCSA can effectively solve this problem.