Autonomous navigation to provide long-distance surface traverses for Mars Rover Sample Return Mission

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 Sample Return Mission. Terrain navigation is accomplished by the following sequence of steps: the skylines from the visibility map and from the local terrain map are compared and the two 3-D curves in space are stochastically matched to update the vehicle location. A path segment is selected taking into consideration the goal, overall 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