Formation Change Strategy of Multiple UAV Based on Improved DQN
Aiming at the problems of complex system structure and large amount of calculation in traditional multiple UAV for-mation transformation methods,a multiple UAV formation transformation method based on improved DQN algorithm is proposed.First,a DQN-based multiple UAV formation transformation method is proposed,and the multiple UAV formation transformation problem is modeled as a Markov decision process.Secondly,the dynamic target point optimal allocation algorithm(DTA)is used to target formation of members in the formation.The optimal node allocation of the formation can improve the efficiency of the formation transformation and accelerate the convergence speed of the DQN algorithm.Again,the introduction of the Reciprocal Velocity Obsta-cle Method(RVO)to guide the formation members to avoid collisions during the formation transformation,thereby improving the performance of the DQN algorithm learning efficiency.Finally,for the unsmooth route planned by the algorithm,the UAV cannot fly,and the three uniform B-spline interpolation algorithm is introduced to smooth the route.In the formation transformation experi-ment,compared with the DQN algorithm based on dynamic target allocation(DTA-DQN),the DQN algorithm based on the recipro-cal speed obstacle method(RVO-DQN),and the traditional DQN algorithm,the convergence speed of the proposed algorithm is in-creased by 39.26%,40.31%,50.77%respectively,and the average range is shorter.The simulation results show that the proposed algorithm can effectively improve the efficiency of multiple UAV formation transformation,and the algorithm has good generalization and practicability.
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