Trajectory Planning of the Unmanned Aerial Vehicles with Adaptive Convex Optimization Method

Abstract In this paper, a constrained unmanned aerial vehicles trajectory optimization problem is formulated. We present an iterative convex programming algorithm to solve the optimal control problem, which consists of both nonlinear dynamics and path constraints. A hp-adaptive pseudospectral method is introduced to transform the original problem into nonlinear programming. Furthermore, in order to improve the computational ability, nonlinear dynamics and path constraints are convexified by convexification techniques. The trajectory planning problem is formulated as a convex programming problem. We evaluate the proposed strategy by some numerical results. The results indicate that the algorithm can get better performance compared with other typical optimal control solvers.