The development of a software system for obstacle avoidance that controls a vehicle smoothly, continuously, and safely across natural terrain en route to a goal is discussed. The work, carried out as part of the Strategic Computing Initiative of the US Defense Advanced Research Projects Agency (DARPA), was performed on the Autonomous Land Vehicle at Martin Marietta's Denver facilities. The planning software uses digital maps to plan a preferred route, and then, as the vehicle traverses that route, sensors are used to obtain scene descriptions. Techniques necessary to detect and avoid obstacles in cross-country terrain, with minimum delay between sensing and acting, are used. The system architecture, the cross-country perception system, the planning system for obstacle avoidance, the simulation environment, and the experiments are described. Work to develop a fine-grained control architecture, internalized plans, multisensor perception, and color image segmentation is discussed.
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