Navigation systems of autonomous vehicles must provide information that enables the control of flight and information about the environment that allows for the perception of the 3-D scene. Passive imaging sensors with the appropriate algorithms can supply both types of information. A concept is presented that evaluates the optical flow field across the image plane in order to derive the quantities necessary for the guidance and control of the vehicle. The quality of information processing is improved by incorporating knowledge of the environment and the dynamics of the vehicle. In various computer simulations, the performance of an observer is compared with an Extended Kalman Filter. The concept is applied to two kinds of unmanned vehicles: to an autonomous unpropelled submunition, which has to detect, to classify, and to track ground vehicles, and to the fiber-optic guided missile that serves as a testbed towards systems of higher autonomy.
Navigation of Autonomous Air Vehicles by Passive Imaging Sensors
1989
14 pages
Report
Keine Angabe
Englisch
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