Adaptive receding horizon control for vision-based navigation of small unmanned aircraft

This paper presents an integrated vision-based navigation system for small autonomous aircraft. Previously developed sensor fusion algorithms based on the unscented Kalman filter (UKF) are combined with an adaptive receding horizon controller (ARHC) for guidance. Control and planning horizons are computed based on the sensor range and the effective speed of the UAV, which is computed as a weighted sum of estimated vehicle speed and time rate of change of the uncertainty of the obstacle position estimates. Simulation results demonstrate the integrated system and illustrate the value of the adaptive approach