Multi-UAVs trajectory and mission cooperative planning based on the Markov model

• Published in: Physical communication 2019-08, Vol.35, p.100717, Article 100717
• Main Authors: Ning, Qian, Tao, Guiping, Chen, Bingcai, Lei, Yinjie, Yan, Hua, Zhao, Chengping
• Format: Article
• Language: English
• Subjects: Collaborative mission planning; Markov model; Meta-heuristic search algorithms; Survival state; Trajectory planning
• ISSN: 1874-4907; 1876-3219
• DOI: 10.1016/j.phycom.2019.100717

As the environment of the battlefield is increasingly complex, single UAV (Unmanned Aerial Vehicle) has trouble in carrying out missions, which requires the cooperation of multiple UAVs. However, search space is very large and search targets are distributed sparsely, and making mission planning and route planning simultaneously is also an NP (Non-Deterministic Polynomial Problems) problem, which makes it extremely difficult in mission planning. Recently, meta-heuristic search algorithms widely used in multi-UAVs collaborative mission planning are difficult to find reliable initial solutions and limit the convergence speed. Aiming at this problem, to take plenty of constraints and performance planning targets in multi-UAV cooperative mission planning problems into full consideration. This paper proposes a two-layer mission planning model based on the simulated annealing algorithm and tabu search algorithm, which solves multi-objectives, Multi-aircraft mission planning problems. This paper combined the five-state Markov chain model with the mission planning model to determine the optimal mission planning scheme by judging the survival state probability of the flight platform. Finally, the simulation results show that this method can greatly improve the survivability of the drone while ensuring optimal mission planning.