Gaussian pseudospectral optimization method with smoothing penalty function path constraint handling for UAV obstacle avoidance planning

Trajectory planning is an important basis for autonomous flight of unmanned aerial vehicle (UAV). A Gaussian pseudospectral trajectory planning algorithm based on smoothing penalty function is proposed. Firstly, the boundary conditions and dynamic constraints of UAV are considered, and the path constraints are studied to establish the trajectory planning dynamic optimization model. Then, smoothing function is introduced to tackle the path constraints and this method is employed to transform the converted constraints. Combined with Gauss-Legendre collocation, the proposed method is given in detail. Finally, simulation experiment is carried out on UAV model. After the simulation experiment, the proposed method has better path constraints satisfaction and performance index than those of traditional Gaussian pseudospectral method.