Multiple concurrent object descriptions in support of autonomous navigation

A sensor system designed to support autonomous navigation should provide a stable, robust model of the environment. We propose and illustrate an approach in which multiple concurrent descriptions of objects are used to construct such a stable model. The principal idea is that several different representations are used to describe the same object in order to support different visual tasks, and to insure an appropriate match between the data, the model, and the task. The use of multiple representations to describe objects requires that the system be able to decide which descriptions of an object are valid. In our approach we use stability over time to indicate validity. To illustrate the power of this approach we have implemented a system, 'TraX', that constructs and refines models of outdoor objects detected in sequences of range data.