STEREO VISION-BASED ESTIMATION OF POSE AND MOTION FOR AUTONOMOUS LANDING OF AN UNMANNED HELICOPTER

Abstract

In this paper, a real-time stereo vision based pose and motion estimation system is presented. It is used for landing an unmanned helicopter on a moving target such as a ship deck. The vision algorithm mainly consists of a feature extraction task and a pose and motion estimation task. By the specially designed pattern of the landing target, the feature extraction algorithm can simplify the step of feature points matching of stereo system. In the task of feature extraction, the step of accurate corner detection can get to the precision of sub-pixel, which helps improve the measurement precision in state estimation. We present results from semi-physical simulation which show that our vision algorithm is accurate and robust to allow our vision sensor to be placed in the control loop of unmanned helicopter management system.