Optimal Sensor Management for Multiple Target Tracking Using Cooperative Unmanned Aerial Vehicles

Abstract

In this work, we consider collaborative unmanned aerial vehicles (UAVs) with a gimbaled sensor tracking multiple mobile surface targets, where the number of targets is greater than the number of UAVs. To this end, we have developed an efficient distributed software algorithm enabling a team of collaborative unmanned aerial vehicles to effectively detect and track multiple mobile ground targets. The software framework we present in this paper includes optimal sensor management technique to minimize the localization uncertainty of targets, efficient data association method, and a consensus decision-making algorithm to reach agreement on target assignments. Our novel strategy in this integrated framework of cooperative aerial robots effectively utilizes their sensing resources using the optimal sensor management technique as well as the consensus decision-making. Our results show that a team of n UAVs can effectively track more than 2n targets with acceptable localization uncertainties.