  In this paper, we propose an approach for assigning an interest level to the
goals of a planetary rover. Assigning an interest level to goals, allows the
rover autonomously to transform and reallocate the goals. The interest level is
defined by data-fusing payload and navigation information. The fusion yields an
"interest map", that quantifies the level of interest of each area around the
rover. In this way the planner can choose the most interesting scientific
objectives to be analyzed, with limited human intervention, and reallocates its
goals autonomously. The Dezert-Smarandache Theory of Plausible and Paradoxical
Reasoning was used for information fusion: this theory allows dealing with
vague and conflicting data. In particular, it allows us directly to model the
behavior of the scientists that have to evaluate the relevance of a particular
set of goals. The paper shows an application of the proposed approach to the
generation of a reliable interest map.
