Simultaneous Localization and Mapping (SLAM) is considered a mature research field with numerous applications and publicly available open-source systems. Despite this maturity,existing SLAM systems often rely on ad-hoc implementations or are tailored to predefined sensor setups. In this work, we tackle these issues, proposing a novel unified SLAM architecture specifically designed to standardize the SLAM problem and to address heterogeneous sensor configurations. Thanks to its modularity and design patterns, the presented framework is easy to extend,maximizes code reuse and improves computational efficiency. We show in our experiments with a variety of typical sensor configurations that these advantages come without compromising state-of-the-art SLAM performance. The result demonstrates the architecture’s relevance for facilitating further research in (multi-sensor) SLAM and its transfer into practical applications.
2020, 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Pages -
Plug-and-Play SLAM: A Unified SLAM Architecture for Modularity and Ease of Use (02a Capitolo o Articolo)
Colosi Mirco, Aloise Irvin, Guadagnino Tiziano, Schlegel Dominik, Della Corte Bartolomeo, Arras Kai O., Grisetti Giorgio