Computer vision assisted autonomous landing of UAV

An analysis of the orientation error for a computer vision assisted integrated navigation scheme for an autonomous landing maneuver of unmanned aerial vehicle (UAV) is presented. The system utilizes the binocular onboard camera fixed on the optoelectronic tracking platform as the sensor to obtain the plan position information. The image processing of the landing system uses such algorithms as template-matching, contour-extraction and featur epoint detection. Since the corners are image points showing strong two dimensional intensity changes while well distinguished from nearby points, the paper establishes a new fast and efficient corner detector based on SUSAN and the feature of corner structure to achieve the corner point detecting task. An algorithm is offered to obtain flight position information based on the knowledge of analytic geometry. The measurement model for the automatic landing system of UAV is deduced according to camera perspective projection theory. Computer simulation results indicate that the navigation scheme could operate properly for the autonomous landing of the UAV.