The aim of the Unmanned Ground Vehicle (UGV) project at the
University of Massachusetts is to develop a system capable of navigating
both on-road and cross country, avoiding obstacles, and determining
its position using landmarks. Complex problems, such as
driving, can be solved more easily by decomposing them into smaller
sub-problems, solving each sub-problem, and then integrating the solutions.
In the case of an autonomous vehicle, the integrated system
should be able to \react" in real time to a changing environment and
to \reason" about ways to achieve its goals. This paper describes the
approach taken on the UMass Mobile Perception Laboratory (MPL)
to integrate independent processes (each solving a particular aspect
of the navigation problem) into a fully capable autonomous vehicle.