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Communication Dans Un Congrès Année : 2020

Dense Decentralized Multi-robot SLAM based on locally consistent TSDF submaps

Résumé

This article introduces a decentralized multi-robot algorithm for Simultaneous Localization And Mapping (SLAM) inspired from previous work on collaborative mapping. This method makes robots jointly build and exchange i) a collection of 3D dense locally consistent submaps, based on a Truncated Signed Distance Field (TSDF) representation of the environment , and ii) a pose-graph representation which encodes the relative pose constraints between the TSDF submaps and the trajectory keyframes, derived from the odometry, inter-robot observations and loop closures. Such loop closures are spotted by aligning and fusing the TSDF submaps. The performances of this method have been evaluated on multi-robot scenarios built from the EuRoC dataset.
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Dates et versions

hal-02995279 , version 1 (09-11-2020)

Identifiants

Citer

Rodolphe Dubois, Alexandre Eudes, Julien Moras, Vincent Frémont. Dense Decentralized Multi-robot SLAM based on locally consistent TSDF submaps. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2020), Oct 2020, Las Vegas, United States. pp.4862-4869, ⟨10.1109/IROS45743.2020.9341680⟩. ⟨hal-02995279⟩
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