  Collaborative Simultaneous Localization And Mapping (C-SLAM) is a vital
component for successful multi-robot operations in environments without an
external positioning system, such as indoors, underground or underwater. In
this paper, we introduce Swarm-SLAM, an open-source C-SLAM system that is
designed to be scalable, flexible, decentralized, and sparse, which are all key
properties in swarm robotics. Our system supports inertial, lidar, stereo, and
RGB-D sensing, and it includes a novel inter-robot loop closure prioritization
technique that reduces communication and accelerates convergence. We evaluated
our ROS-2 implementation on five different datasets, and in a real-world
experiment with three robots communicating through an ad-hoc network. Our code
is publicly available: https://github.com/MISTLab/Swarm-SLAM
