SLAM Back-End

We released an open-source C++ plugin for g2o that implements our back-end approach. Moreover, we provide a simulator to generate matchable graphs using the g2o framework. Code is available [here].

SLAM Front-End

We developed a simplistic front-end for RGB-D data to validate the usability of such a back-end on graphs generated from real data. We extendended the SA-SHA system, adding to the front-end the option to “export” the generated factor graph. Additionally, we implemented a straighforward loop detection on top of the recent Visual Place Recognition (VPR) library HBST. Code is available [here].

Publications

This works has been accepted to RSS 19 and RA-L. Please cite our most recent article when using SA-SHAGO: 


@article{aloise2019systematic,
  title={Systematic Handling of Heterogeneous Geometric Primitives in Graph-SLAM Optimization},
  author={Aloise, Irvin and Della Corte, Bartolomeo and Nardi, Federico and Grisetti, Giorgio},
  journal={IEEE Robotics and Automation Letters},
  volume={4},
  number={3},
  pages={2738--2745},
  year={2019},
  publisher={IEEE}
}
[DOI: 10.1109/LRA.2019.2918054]

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