Applying a new model for machine perception and reasoning in unstructured environments

This paper presents a data-fusion and interpretation system for operation of an Autonomous Ground Vehicle (AGV) in outdoor environments. It is a practical implementation of a new model for machine perception and reasoning, which has its true utility in its applicability to increasingly unstructured environments. This model provides a cohesive, sensor-centric and probabilistic summary of the available sensory data and uses this richly descriptive data to enable robust interpretation of a scene. A general model is described and the development of a specific instance of it is described in detail. Preliminary results demonstrate the utility of the approach in very large, unstructured, outdoor environments.