Optimal Control of Constrained Trajectory Optimization Problem of UAV with Limited Sensing

Optimal control of constrained unmanned aerial vehicle (UAV) trajectory optimization problem is one of the frontiers and hotspots of UAV research. The various constraints generated by physical limitations and obstacles in the environment increase the difficulties of solving the trajectory optimization problem, especially when the limited sensing ability is taken into consideration. This paper presents the receding horizon optimization method to obtain optimal control for the UAV with limited sensing range in a complex environment with obstacles. To improve efficiency, a path constraint processing method is proposed to reduce the number of constraints in the nonlinear programming problem (NLP). The proposed main structure and detailed algorithm are also given. The numerical results demonstrate the effectiveness of the proposed method compared with the classical Gauss pseudospectral method.