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

Pierre–Yves Lajoie, Giovanni Beltrame

2023IEEE Robotics and Automation Letters146 citationsDOI

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.

Topics & Concepts

Simultaneous localization and mappingSwarm behaviourRobotComputer scienceArtificial intelligenceComputer visionMobile robotRobotics and Sensor-Based LocalizationModular Robots and Swarm IntelligenceRobotic Path Planning Algorithms
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