Abstract
The 4D approach to dynamic machine vision has been validated for the application area of on-board autonomous landing approaches in the visual flight regime with computing technology available today; sensors are a video-camera, inertial gyros and an air velocity meter. The key feature of the method is the reconstruction and servo-maintained adjustment by prediction error feedback of an internal spatiotemporal model about the process to be controlled. This encompasses both the egomotion state of the aircraft carrying the sensors and the relevant geometric properties of the runway and its spatial environment. The efficiency of the approach is proved both in a hardware-in-the-loop simulation and in real test flights with a twin turbo-prop aircraft. For accuracy evaluation of the data gathered, the results of differential GPS and radiometric altitude measurements have been recorded simultaneously.
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Schell, F.R., Dickmanns, E.D. Autonomous landing of airplanes by dynamic machine vision. Machine Vis. Apps. 7, 127–134 (1994). https://doi.org/10.1007/BF01211658
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DOI: https://doi.org/10.1007/BF01211658