Dickmanns and Wuensche 1986b : Using a 2D-satellite model plant (air-cushion vehicle with reaction jet control) automatic rendezvous and docking maneuvers have been investigated with real image processing hardware in the loop. The docking partner is completely passive; its 3D shape is considered to be known and coded by a wire frame model in the knowledge base. Image processing is done in real-time on a custom made multi-microprocessor MIMD computer system. Object recognition is achieved by feature aggregation exploiting the laws of perspective projection. During the approach and circumnavigation maneuvers, features are automatically tracked using dynamical models of the process for prediction, data filtering and control. A sequential Kalman filter formulation is used to accommodate the time varying length of the feature vector due to occlusion, failures and redirection of processing elements by the knowledge base. A method has been devised to always select that feature vector yielding the best state estimate. The system runs at 0.13 second cycle time (8 video frames per control cycle) and performs physical docking with a static rendezvous partner. Experimental results are given as time charts and video film sequences.
The visual guidance scheme developed, combining dynamical models and perspective projection, is considered to be a powerful and effective general method for motion control by computer vision.