A current project of great import to the National Aeronautics and Space Administration is the development of an automated docking and tracking system to facilitate autonomous operations in space. Such a system would have to be able to determine the relative positions, velocities, and orientations of a multitude of bodies. A stereoscopic vision system was developed to implement an automated docking solution. This system used artificial neural networks to identity beacons or fixed points on the objects to be tracked. Specifically, this research sought to solve the problems inherent in the planned 1995 docking of the U.S. Space Shuttle to the former Soviet Space Station Mir. In addition to the basics of an optical ranging and object-recognition system, a simple user interface for operation monitoring was designed. Specifically, the coordinates of the space station, shuttle waypoints, and smooth trajectory position, velocity, and acceleration information were calculated and displayed. A mock docking was also simulated, with the vision system providing the range and orientation data. By placing the vision system at known coordinates and checking its computed trajectory, the accuracy of the algorithms and given hardware were checked. Space docking and tracking systems, Stereoscopic vision systems, Object-recognition systems, Automated systems.
Stereoscopic Vision System with Applications to Automated Docking and Tracking
1993
80 pages
Report
Keine Angabe
Englisch
Manned Spacecraft , Astronautics , Robotics/Robots , Docking , Space shuttles , Tracking , Autonomous navigation , Acceleration , Accuracy , Aeronautics , Algorithms , Beacons , Coordinates , Interfaces , Management , Monitoring , Networks , Neural nets , Recognition , Space stations , Stations , Trajectories , Velocity , Vision , Computer vision
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