Minimum path deviation rapid online path planning of unmanned aerial vehicles with avoidance zones constraints

This paper investigates a minimum path deviation online path planning problem for UAV with constrainted avoidance zones. The nonlinear and nonconvex of this problem make the path planning is very time consuming and not acceptable for using onboard. Three new state variables and two control variables are redefined to convert the nonconvex problem into a second-order cone convex programming problem, which can be solved in polynomial time by primal-dual interior-point method, theoretical proof demonstrates the equivalence of the relaxed convex problem and the original problem. We propose a sequential second-order cone programming algorithm in order to get the optimal solution of the convexified problem. Numerical simulations show the effectiveness and less time-consuming of the proposed algorithm, no initial guess required and efficient solving process indicate that the algorithm has potential future for online path planning applications.