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Acta Aeronautica et Astronautica Sinica ›› 2023, Vol. 44 ›› Issue (S1): 727354-727354.doi: 10.7527/S1000-6893.2022.27354

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Task assignment algorithm for intelligent missile swarm based on PSO and RRT

Yunchong ZHU1,2, Yangang LIANG1,2(), Kebo LI1,2, Yuanhe LIU1,2   

  1. 1.College of Aerospace Science and Engineering,National University of Defense Technology,Changsha  410073,China
    2.Hunan Key Laboratory of Intelligent Planning and Simulation for Aerospace Mission,National University of Defense Technology,Changsha  410073,China
  • Received:2022-04-30 Revised:2022-05-13 Accepted:2022-07-01 Online:2023-06-25 Published:2022-07-08
  • Contact: Yangang LIANG E-mail:liangyg@nudt.edu.cn
  • Supported by:
    National Natural Science Foundation of China(12002370)

Abstract:

A new particle structure of Particle Swarm Optimization (PSO) is proposed to solve the task assignment problem of the intelligent missile swarm. Firstly, the battlefield situation information is introduced to determine the task time window of the intelligent missile swarm, and further integrated into the task allocation mathematical model. Secondly, based on the Rapidly-exploring Random Trees (RRT) algorithm, the flight path planning of avoiding no-fly zones is completed in the task assignment stage to reduce the difference between the actual distance and the estimated distance, and to ensure the rationality of the assignment result, so that the optimized results are more practical. Finally, the proposed algorithm is compared with the results of the genetic algorithm and tabu search algorithm under different task scales, and the simulation results verify that the proposed method has simple principles, fewer parameters, lower calculation costs, and is easier to apply in practical engineering of intelligent loitering munition swarm task assignment problems.

Key words: intelligent missile swarm, task assignment, particle swarm optimization, particle structure, Rapidly-exploring Random Trees (RRT)

CLC Number: