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The task addressed in this article is the localization of an unknown number of targets using a mobile robot equipped with a visual sensor. The estimation of the number of targets and their locations is done using a recursive Bayesian filter over random finite sets (RFSs), and the position of the robot is assumed to be known. We present a computationally tractable control law whereby the robot follows the gradient of mutual information between target locations and detections. The method is verified through real-world experimental trials, reliably detecting multiple targets and ignoring clutter obstacles.