Knowledge acquisition and representation techniques are developed to allow an autonomous vehicle to negotiate a path over partially unknown terrain, such as the long-distance traverses for the Mars Rover Saayle Return Mission. Terrain navigation is accomplished by the following sequence of steps: The skylines from the visibility map and from the space are stochastically matched to update the vehicle location. A path-segment is selected taking into co"ion the goal, o v d global topography. obstacles such as craters and boulders derived from the range-finder observations, and a priori constraints related to the mission, fuel consumption, and vehicle stability. The vehicle reaches a new vantage point with relatively broad visibility, but within sight of the last observation point. The skyline is then estimated and approximated again, and the cycle is reiterated for another advance. local terrain map are compared and the two 3-D CUIV~S io
SurmnaryFor on-line estimation of the parameters of a system w i t h unknown impulse inputs , Kalman f i l t e r does not perform adequately. A scheme has been developed t o detect and estimate the impulse changes and thus obtain a rapid estimate.An example shows t h e d e s i r a b i l i t y o f the new method.
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