Swarm-SLAM: Sparse Decentralized Collaborative Simultaneous Localization and Mapping Framework for Multi-Robot Systems
Pierre-Yves Lajoie, Giovanni Beltrame
Abstract
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 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.
BibTeX
@inproceedings{ral2024_swarmslamsparsed,
title = {Swarm-SLAM: Sparse Decentralized Collaborative Simultaneous Localization and Mapping Framework for Multi-Robot Systems},
author = {Pierre-Yves Lajoie and Giovanni Beltrame},
booktitle = {RA-L 2024},
year = {2024}
}