The authors present an operational perception system for cross-country navigation which has been verified in both simulated and real-world environments. Range data from a laser range scanner is transformed into an alternate representation called the Cartesian elevation map (CEM). A detailed vehicle model operates on the CEM to produce traversability information along selected trajectories. This information supports a real-time reflexive planning system. The authors successfully demonstrated their obstacle detection and avoidance algorithms on board the autonomous land vehicle at Martin Marietta Aerospace Corporation in Denver. They also propose enhancements to their current operational system.>

A description is given of the first cross-country map and sensor-based autonomous operation of a robotic vehicle. Experiments on the autonomous land vehicle (ALV) in natural terrain were performed. An overview of the software architecture is provided, and details of the perception and planning techniques are presented. Two key experiments in which the vehicle avoided known and unknown obstacles in its path are described.>