Plug-and-Play SLAM: A Unified SLAM Architecture for Modularity and Ease of Use
This work addresses the issue of inflexibility in SLAM systems for robotics, enabling easier adaptation to heterogeneous sensors, though it is incremental in improving modularity rather than foundational.
The authors tackled the problem of SLAM systems being ad-hoc and tied to specific sensor configurations by proposing a novel modular architecture that standardizes solutions and enhances code reuse, achieving competitive state-of-the-art performance in experiments across various sensor setups.
Nowadays, SLAM (Simultaneous Localization and Mapping) is considered by the Robotics community to be a mature field. Currently, there are many open-source systems that are able to deliver fast and accurate estimation in typical real-world scenarios. Still, all these systems often provide an ad-hoc implementation that entailed to predefined sensor configurations. In this work, we tackle this issue, proposing a novel SLAM architecture specifically designed to address heterogeneous sensors' configuration and to standardize SLAM solutions. Thanks to its modularity and to specific design patterns, the presented architecture is easy to extend, enhancing code reuse and efficiency. Finally, adopting our solution, we conducted comparative experiments for a variety of sensor configurations, showing competitive results that confirm state-of-the-art performance.