The overall objective of the Wallenberg Laboratory for Information Technology and Autonomous Systems (WITAS) at Linkoping University is the development of an intelligent command and control system, containing active-vision sensors, which supports the operation of an unmanned air vehicle (UAV). One of the UA V platforms of choice is the R5O unmanned helicopter, by Yamaha.
The present version of the UAV platform is augmented with a camera system. This is enough for performing missions like site mapping, terrain exploration, in which the helicopter motion can be rather slow. But in tracking missions, and obstacle avoidance scenarios, involving high-speed helicopter motion, robust performance for the visual-servoing scheme is desired. Robustness in this case is twofold: 1) w.r.t time delays introduced by the image processing; and 2) w.r.t disturbances, parameter uncertainties and unmodeled dynamics which reflect on the feature position in the image, and the camera pose.
With this goal in mind, we propose to explore the possibilities for the design of fuzzy controllers, achieving stability, robust and minimal-cost performance w.r.t time delays and unstructured uncertainties for image feature tracking, and test a control solution in both simulation and on real camera platforms. Common to both are model-based design by the use of nonlinear control approaches. The performance of these controllers is tested in simulation using the nonlinear geometric model of a pin-hole camera. Then we implement and test the reSUlting controller on the camera platform mounted on the UAV.