Directional sensors are gaining importance due to applications, in- cluding surveillance, detection, and tracking. Such sensors have a limited field-of-view and a discrete set of directions they can be pointed to. The Directional Sensor Control problem (DSCP) consists in assigning a direction of view to each sensor. The location of the targets is known with uncertainty given by a joint prior Gaussian distribution, while sensor locations are known exactly. In this paper we study exact and heuristic approaches for the DSCP with the goal of maximizing information gain on the location of a given set of immobile target objects. In particular, we propose an exact mixed integer convex programming (MICP) formulation to be solved by a black-box MICP solver and several meta-heuristic approaches based on local search. A computational evaluation shows the very good performance of both methods.
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