Ricerc@Sapienza

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.

A Simultaneous Localization and Mapping(SLAM) system is a complex program consisting of several interconnected components with different functionalities such as optimization, tracking or loop detection. Whereas the literature addresses in detail how enhancing the algorithmic aspects ofthe individual components improves SLAM performance, the modal aspects, such as when to localize, relocalize or close a loop, are usually left aside.