English

Swarm-SLAM : Sparse Decentralized Collaborative Simultaneous Localization and Mapping Framework for Multi-Robot Systems

Robotics 2024-01-17 v3 Computer Vision and Pattern Recognition

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 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

Keywords

Cite

@article{arxiv.2301.06230,
  title  = {Swarm-SLAM : Sparse Decentralized Collaborative Simultaneous Localization and Mapping Framework for Multi-Robot Systems},
  author = {Pierre-Yves Lajoie and Giovanni Beltrame},
  journal= {arXiv preprint arXiv:2301.06230},
  year   = {2024}
}

Comments

Code: https://github.com/MISTLab/Swarm-SLAM

R2 v1 2026-06-28T08:12:14.910Z