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Active Search and Tracking for search and rescue missions or collaborativemobile robotics relies on the actuation of a sensing platform to detect andlocalize a target. In this paper we focus on visually detecting aradio-emitting target with an aerial robot equipped with a radio receiver and acamera. Visual-based tracking provides high accuracy, but the directionality ofthe sensing domain may require long search times before detecting the target.Conversely, radio signals have larger coverage, but lower tracking accuracy.Thus, we design a Recursive Bayesian Estimation scheme that uses cameraobservations to refine radio measurements. To regulate the camera pose, wedesign an optimal controller whose cost function is built upon a probabilisticmap. Theoretical results support the proposed algorithm, while numericalanalyses show higher robustness and efficiency with respect to visual andradio-only baselines.

Probabilistic Radio-Visual Active Sensing for Search and Tracking