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

翻译：合作同步本地化和绘图(C-SLAM)是在没有外部定位系统的环境中(如室内、地下或水下)成功进行多机器人操作的关键组成部分,本文介绍Swarm-SLAM,这是一个开放源码的C-SLAM系统,其设计是可扩展、灵活、分散和分散的,是群温机器人的所有关键特性。我们的系统支持惯性、lidar、立体和RGB-D感测,它包括一种新型的跨机器人循环闭合技术,减少通信和加速汇合。我们评估了我们关于五个不同数据集的ROS-2执行情况,并在现实世界试验中与三个机器人通过ad-hoc网络进行交流。我们的代码公开提供:https://github.com/MISTLab/Swarm-SLAM。