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We present the design and implementation of a real-time computer vision system for a rotor-craft unmanned aerial vehicle to land onto a known landing target. This vision system consists of customized software and off-the-shelf hardware which perform image processing, segmentation, feature point extraction, camera pan/tilt control, and motion estimation. We introduce the design of a landing target which significantly simplifies the computer vision tasks such as corner detection and correspondence matching. Customized algorithms are developed to allow for realtime computation at a frame rate of 30Hz. Such algorithms include certain linear and nonlinear optimization schemes for model-based camera pose estimation. We present results from an actual flight test which show the vision-based state estimates are accurate to within 5cm in each axis of translation and 5 degrees in each axis of rotation, making vision a viable sensor to be placed in the control loop of a hierarchical flight management system.
Sharp et al. (Wed,) studied this question.