H.4.2 HIL-Sim AirVehGuidance
H.4.2a Landing approaches with vector graphics
With the increasing computing power per micro-processor of about one order of magnitude every 4 to 5 years, image analysis with the BVV2 could be improved considerably towards the end of the 1980’s. The figure shows 10 evaluation windows which allowed determining each border line of the landing strip independent of a strictly rectangular shape in the real world.
This improved system was tuned to the bi-propeller aircraft Dornier Do 128 and fully tested in HIL-simulation. This allowed starting real flight experiments in 1991 within one week from access to the aircraft in Brunswick.
Video 12 AircraftLandingApproach 1982– 92
H.4.2b Landing approaches with Computer Generated Images (CGI), 1992 – 1998
These CGI – systems allow much more natural-appearing images than vector graphics; the image evaluation task is much closer to what is needed for real flight scenes.
Left: Imaged with standard lens; right: imaged with tele-lens; search paths (red) and extracted edge features (black) are superimposed.
video 24 HelicopterMissionBsHIL-Sim 1997
Schell FR (1992). Bordautonomer automatischer Landeanflug aufgrund bildhafter und inertialer Meßdatenauswertung, Dissertation, UniBwM / LRT. Kurzfassung
Werner S, Buchwieser A, Dickmanns ED (1995). Real-Time Simulation of Visual Machine Perception for Helicopter Flight Assistance. Proc. SPIE - Aero Sense, Orlando, FL
Dickmanns ED (1997). Parallels between simulation techniques for vehicle motion and perceptual integration in autonomous vehicles. Proc. European Simulation Symposium (ESS’97), Passau, pp 5-12
Fürst S, Werner S, Dickmanns ED (1997). Autonomous Landmark Navigation and Landing Approach with Obstacle Detection for Aircraft. 10th European Aerospace Conference ‘Free Flight’, Amsterdam, NL, pp 36.1 – 36.11
Werner S (1997). Maschinelle Wahrnehmung für den bordautonomen automatischen Hubschrauberflug. Diss., UniBwM / LRT. Kurzfassung