Knowledge about the own pose is key for all mobile robot applications. Thus
pose estimation is part of the core functionalities of mobile robots. In the
last two decades, LiDAR scanners have become a standard sensor for robot
localization and mapping. This article surveys recent progress and advances in
LiDAR-based global localization. We start with the problem formulation and
explore the application scope. We then present the methodology review covering
various global localization topics, such as maps, descriptor extraction, and
consistency checks. The contents are organized under three themes. The first is
the combination of global place retrieval and local pose estimation. Then the
second theme is upgrading single-shot measurement to sequential ones for
sequential global localization. The third theme is extending single-robot
global localization to cross-robot localization on multi-robot systems. We end
this survey with a discussion of open challenges and promising directions on
global lidar localization