On UAV routing protocols for sparse sensor data exfiltration

The problem addressed in this paper is data exfiltration from a collection of sensors that are unable to establish ad-hoc communication due to their widespread deployment, geographical constraints, and power considerations. Sensor data is exfiltrated by one or more uninhabited aerial vehicles (UAVs) that act as data mules by visiting each sensor in order to establish a communication link. In many applications, the sequence in which the UAVs visit the sensors can have large impact on the overall performance because some sensors have more informative data than others and because distant nodes take a long time to visit. One such application that we will focus on in this paper is the acoustic source localization problem in which the objective is to localize the source of a transient acoustic event as quickly as possible. We introduce two protocols, ACM and TTM, based on receding horizon optimization of the volume of the Cramer-Rao uncertainty ellipsoid and show significant performance benefits over several other routing protocols using a high-fidelity online simulation environment.