  We present a novel scalable, fully distributed, and online method for
simultaneous localisation and extrinsic calibration for multi-robot setups.
Individual a priori unknown robot poses are probabilistically inferred as
robots sense each other while simultaneously calibrating their sensors and
markers extrinsic using Gaussian Belief Propagation. In the presented
experiments, we show how our method not only yields accurate robot localisation
and auto-calibration but also is able to perform under challenging
circumstances such as highly noisy measurements, significant communication
failures or limited communication range.
