maplab 2.0 - A Modular and Multi-Modal Mapping Framework

卷:8

Article

关键词: SIMULTANEOUS LOCALIZATION;    ONLINE;    FILTER;    SLAM;   

DOI  :  10.1109/LRA.2022.3227865

来源: SCIE

【 摘 要 】

Integration of multiple sensor modalities and deep learning into Simultaneous Localization And Mapping (SLAM) systems are areas of significant interest in current research. Multi modality is a stepping stone towards achieving robustness in challenging environments and interoperability of heterogeneous multi robot systems with varying sensor setups. With maplab 2.0, we provide a versatile open-source platform that facilitates developing, testing, and integrating new modules and features into a fullyfledged SLAM system. Through extensive experiments, we show that maplab 2.0's accuracy is comparable to the state-of-the-art on the HILTI 2021 benchmark. Additionally, we showcase the flexibility of our system with three use cases: i) large-scale (similar to 10 km) multi-robot multi-session (23 missions) mapping, ii) integration of non-visual landmarks, and iii) incorporating a semantic object-based loop closure module into the mapping framework.

【 授权许可】

Free