Systems Engineering and Electronics ›› 2023, Vol. 45 ›› Issue (4): 1098-1110.doi: 10.12305/j.issn.1001-506X.2023.04.18

• Systems Engineering • Previous Articles    

Deck path planning algorithm of carrier-based aircraft based on heuristic and optimal control

Wei HAN1, Zixuan LIU1, Xichao SU1,*, Kaikai CUI2, Jie LIU3   

  1. 1. Aviation Foundation College, Naval Aeronautical University, Yantai 264001, China
    2. Unit 92942 of the PLA, Beijing 100161, China
    3. War Research Institute, Academy of Military Science, Beijing 100850, China
  • Received:2022-01-13 Online:2023-03-29 Published:2023-03-28
  • Contact: Xichao SU

Abstract:

Carrier-based aircraft deck routing is a key step in the full-cycle dispatching and recovery operation of aircraft fleets. In order to improve the efficiency of carrier-based aircraft transfer, the optimal path satisfying the kinematic and terminal position constraints is obtained as the goal, and the heuristic and optimal control methods are combined to conduct the deck path planning research of carrier-based aircraft. Firstly, a convex hull obstacle expansion model is established for the complex deck layout environment. Secondly, a dynamic measurement factor is introduced into the A* algorithm and the trajectory re-search algorithm is designed to solve the shortest path key point. Finally, the motion state of the key point is solved and combined with the optimal control algorithm to plan and integrate the segmented paths between the key points. The simulation experiments of path planning under typical deck environment are carried out to verify the superiority of the proposed algorithm by comparing with the simulation results of the optimal control algorithm. The simulation experimental results show that the proposed algorithm effectively solves the problem of initial value sensitivity of the optimal control algorithm in the complex obstacle environment, and effectively improves the optimization performance of the deck transfer.

Key words: carrier-based aircraft, flight deck, path planning, A* algorithm, optimal control

CLC Number: 

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