Multirobot Localisation Using Interlaced Extended Kalman Filter

This paper deals with a new approach to multi robot localization. An Interlaced extended Kalman filter is shown to be a good solution to the problem of estimating the pose of a team of robots with a fully decentralized algorithm. Moreover, it is feasible to dynamically "correct" the estimation autonomously evaluated by each single robot, updating this quantity anytime two robots randomly come across. The algorithm combines the robustness of a full state EKF with the simplicity of its interlaced implementation. It does not need global supervision, and allows a large flexibility in using exteroceptive sensors. The paper presents some simulations to show the feasibility of the approach considering a set of robots equipped with different combinations of sensors and with wireless communication devices able to support data exchange when they are sufficiently clos