Aerial recovery trajectory optimization is to obtain a recovery trajectories that satisfy the cost function optimally according to initial conditions, target points, and constraints during air recovery, which are used as reference trajectories to guide the drogue-UAV assembly to complete aerial recovery. It needs to minimize recovery time and improve recovery efficiency, taking into account constraints such as safety, flight performance, etc. In this paper, an optimal model of time optimal air recovery trajectory is constructed, and an improved sequential convex optimization algorithm with adaptive trust region constraints is proposed. The simulation results show that the adaptive trust region constraints can effectively improve the convergence of the sequential convex optimization method.

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Trajectory Optimization for UAV Towed Recovery Based on Sequential Convex Optimization

  • Guocheng Yan,
  • Honglun Wang,
  • Yanxiang Wang,
  • Junfan Zhu

摘要

Aerial recovery trajectory optimization is to obtain a recovery trajectories that satisfy the cost function optimally according to initial conditions, target points, and constraints during air recovery, which are used as reference trajectories to guide the drogue-UAV assembly to complete aerial recovery. It needs to minimize recovery time and improve recovery efficiency, taking into account constraints such as safety, flight performance, etc. In this paper, an optimal model of time optimal air recovery trajectory is constructed, and an improved sequential convex optimization algorithm with adaptive trust region constraints is proposed. The simulation results show that the adaptive trust region constraints can effectively improve the convergence of the sequential convex optimization method.