Relative localization and identification in a heterogeneous multi-robot system

We develop a localization method for a single-UAV/multi-UGV heterogeneous system of robots. Considering the natural supervisory role of the UAV and the challenging (but realistic) assumption that the UAV-to-UGV measurements do not include the identities of the UGVs, we have adopted the PHD filter as a multi-target tracking technique. However, the standard version of this filter does not take into account odometric information coming from the targets, nor does it solve the problem of estimating their identities. Hence, we design ID-PHD, a modification of the PHD filter that is able to reconstruct the identities of the targets by incorporating odometric data. The proposed localization method has been successfully validated through experiments. Some preliminary results of a localization-based control scheme for the multi-robot system are also presented.