Initial results from vision-based control of the Ames Marsokhod rover

A terrestrial geologist investigates an area by systematically moving among and inspecting surface features, such as outcrops, boulders, contacts and faults. A planetary geologist must explore remotely and use a robot to approach and image surface features. To date, position-based control has been developed to accomplish this task. This method requires an accurate estimate of the feature position, and frequent update of the robot's position. In practice this is error prone, since it relies on interpolation and continuous integration of data from inertial or odometric sensors or other position determination techniques. The development of vision-based control of robot manipulators suggests an alternative approach for mobile robots. We have developed a vision-based control system that enables our Marsokhod mobile robot to drive autonomously to within sampling distance of a visually designated natural feature. This system utilizes a robust correlation technique based on matching the sign of the difference of the Gaussian of images. We will describe our system and our initial results using it during a field experiment in the Painted Desert of Arizona.