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

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arxiv 2301.06230 v3 pith:NYCHJTHK submitted 2023-01-16 cs.RO cs.CV

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

classification cs.RO cs.CV
keywords swarm-slamsystemc-slamcollaborativedecentralizedlocalizationmappingmulti-robot
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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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

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. MR-SLAM: Immersive Spatial Supervision for Multi-Robot Mapping via Mixed Reality

    cs.RO 2026-05 unverdicted novelty 4.0

    MR-SLAM combines passthrough mixed reality with multi-robot SLAM on ROS 2 to let one operator supervise mapping in situ, reporting 8.83 Hz scans, 17.9 m² coverage, and 94.7% occupancy consistency in simulated sessions.