Name
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 spatio-temporal 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 Do 128 of Dornier. For accuracy evaluation of the data gathered, the results of differential GPS and radiometric altitude measurements have been recorded simultaneously |
Year | DOI | Venue |
|---|---|---|
1992 | 10.1109/ACV.1992.240314 | Palm Springs, CA |
Keywords | Field | DocType |
aerospace computer control,aircraft control,computer vision,mobile robots,air velocity meter,autonomous landing,differential GPS,dynamic machine vision,inertial gyros,prediction error feedback,radiometric altitude measurements,test-flights,visual flight regime | Inertial frame of reference,Computer vision,Extended Kalman filter,Visual flight,Machine vision,Simulation,Computer science,Air velocity,Artificial intelligence,Runway,Differential GPS,Mobile robot | Conference |
Citations | PageRank | References |
19 | 7.06 | 2 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ernst D. Dickmanns | 1 | 262 | 57.01 |
| Schell, F.-R. | 2 | 19 | 7.06 |