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

About

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

Pierre-Yves Lajoie, Giovanni Beltrame• 2023

Related benchmarks

TaskDatasetResultRank
TrackingAriaMultiagent
ATE RMSE4.29
30
SLAM TrackingReplicaMultiagent
Off-0 Score1.76
15
Trajectory trackingMulti-agent Replica Apartment-1
ATE RMSE (cm)4.62
15
Trajectory trackingMulti-agent Replica Office-0-C
ATE RMSE (cm)1.07
15
Trajectory trackingMulti-agent Replica Apartment-2
ATE RMSE (cm)2.69
15
Trajectory trackingMulti-agent Replica Apartment-0
ATE RMSE (cm)1.61
12
Trajectory trackingMulti-agent Replica Average
ATE RMSE (cm)2.5
12
SLAMS3E Campus sequence
Sequence Length (N)29
9
SLAMS3E Teaching sequence
Sequence Length (N)110
9
SLAMS3E Square sequence
Sequence Length (N)7
9
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