Receding horizon guidance of a small unmanned aerial vehicle for planar reference path following

Abstract This paper describes a novel lateral guidance law for an unmanned aerial vehicle using nonlinear receding horizon optimization and shows its flight test results. The guidance law uses an extended Kalman filter which estimates steady wind velocities in order to follow a pre-specified reference path defined in a ground-fixed coordinate system. The guidance law can be applied to arbitrary reference path as long as the path is represented as a differentiable function of x and y in a ground-fixed coordinate system. A small-scale research vehicle developed by the Japan Aerospace Exploration Agency is used for flight tests, and the results demonstrate the high guidance performance of the proposed method.