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.