Multi S-graphs: A Collaborative Semantic SLAM architecture.

Miguel Fernandez Cortizas, Hriday Bavle, Jose Luis Sanchez-Lopez, Pascual Campoy, Holger Voos

Keywords: Collaborative SLAM, Graph SLAM, Distributed SLAM

TL;DR: "In this work, we present Multi S-Graphs, an graph based distributed Colaborative SLAM algorithm that utilizes high-level semantic information for cooperative map generation."

Abstract: Collaborative Simultaneous Localization and Mapping (CSLAM) is a critical capability for enabling multiple robots to operate in complex environments. Most CSLAM techniques rely on the transmission of low-level features for visual and LiDAR-based approaches, which are used for pose graph optimization. However, these low-level features can lead to incorrect loop closures, negatively impacting map generation. Recent approaches have proposed the use of high-level semantic information in the form of Hierarchical Semantic Graphs to improve the loop closure procedures and overall precision of SLAM algorithms. In this work, we present Multi S-Graphs, an S-graphs based distributed CSLAM algorithm that utilizes high-level semantic information for cooperative map generation while minimizing the amount of information exchanged between robots. Experimental results demonstrate the promising performance of the proposed algorithm in map generation tasks.