  Global localization is essential in enabling robot autonomy, and
collaborative localization is key for multi-robot systems. In this paper, we
address the task of collaborative global localization under computational and
communication constraints. We propose a method which reduces the amount of
information exchanged and the computational cost. We also analyze, implement
and open-source seminal approaches, which we believe to be a valuable
contribution to the community. We exploit techniques for distribution
compression in near-linear time, with error guarantees. We evaluate our
approach and the implemented baselines on multiple challenging scenarios,
simulated and real-world. Our approach can run online on an onboard computer.
We release an open-source C++/ROS2 implementation of our approach, as well as
the baselines
