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A Two-Stage Method for UCAV TF/TA Path Planning Based on Approximate Dynamic Programming

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  • Hao-xiang Chen
  • Ying Nan
  • Yi Yang

Abstract

We present a two-stage method for solving the terrain following (TF)/terrain avoidance (TA) path-planning problem for unmanned combat air vehicles (UCAVs). The 1st stage of planning takes an optimization approach for generating a 2D path on a horizontal plane with no collision with the terrain. In the 2nd stage of planning, an optimal control approach is adopted to generate a 3D flyable path for the UCAV that is as close as possible to the terrain. An approximate dynamic programming (ADP) algorithm is used to solve the optimal control problem in the 2nd stage by training an action network to approximate the optimal solution and training a critical network to approximate the value function. Numerical simulations indicate that ADP can determine the optimal control variables for UCAVs; relative to the conventional optimization method, the optimal control approach with ADP shows a better performance under the same conditions.

Suggested Citation

  • Hao-xiang Chen & Ying Nan & Yi Yang, 2018. "A Two-Stage Method for UCAV TF/TA Path Planning Based on Approximate Dynamic Programming," Mathematical Problems in Engineering, Hindawi, vol. 2018, pages 1-11, September.
    • Handle: RePEc:hin:jnlmpe:1092092
    DOI: 10.1155/2018/1092092
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    Cited by:

    1. Haoran Zhu & Yunhe Wang & Zhiqiang Ma & Xiangtao Li, 2021. "A Comparative Study of Swarm Intelligence Algorithms for UCAV Path-Planning Problems," Mathematics, MDPI, vol. 9(2), pages 1-31, January.

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