BeliefDriven Control Policy of a Drone with Microphones for Multiple Sound Source Search This paper proposes a beliefdriven control policy of a drone with microphones for multiple sound source search. As the sound source localization by drones is uncertain because of the observation significantly distorted by noise such as rotor noise, the belief on the estimated targets may consist of multiple peaks that are spread over the bounded search area. The proposed control policy is formulated with a robust cost function so that the function encodes the search mission properly. A peak management mechanism is additionally introduced to keep tracking all targets by masking sufficiently observed and well estimated targets whose peaks normally become steep and high. The proposed control policy was evaluated by numerical simulations, and experiments, and those results have validated the efficacy of the proposed control policy.

Audiovisual sensing from a quadcopter: dataset and baselines for source localization and sound enhancement We present an audiovisual dataset recorded outdoors from a quadcopter and discuss baseline results for multiple applications. The dataset includes a scenario for source localization and sound enhancement with up to two static sources, and a scenario for source localization and tracking with a moving sound source. These sensing tasks are made challenging by the strong and timevarying egonoise generated by the rotating motors and propellers. The dataset was collected using a small circular array with 8 microphones and a camera mounted on the quadcopter. The camera view was used to facilitate the annotation of the soundsource positions and can also be used for multimodal sensing tasks. We discuss the audiovisual calibration procedure that is needed to generate the annotation for the dataset, which we make available to the research community1.1http:cis.eecs.qmul.ac.ukprojectsavq