Voxblox++ is a framework for incrementally building volumetric object-centric maps during online scanning with a localized RGB-D camera. Besides accurately describing the geometry of the reconstructed scene, the built maps contain information about the individual object instances observed in the scene. In particular, the proposed framework retrieves the dense shape and pose of recognized semantic objects, as well as of newly discovered, previously unobserved object-like instances.
More information and sample datasets can be found in the wiki pages.
The Voxblox++ framework is described in the following publication:
@article{grinvald2019volumetric,
author={M. {Grinvald} and F. {Furrer} and T. {Novkovic} and J. J. {Chung} and C. {Cadena} and R. {Siegwart} and J. {Nieto}},
journal={IEEE Robotics and Automation Letters},
title={{Volumetric Instance-Aware Semantic Mapping and 3D Object Discovery}},
year={2019},
volume={4},
number={3},
pages={3037-3044},
doi={10.1109/LRA.2019.2923960},
ISSN={2377-3766},
month={July},
}
The original geometry-only framework was introduced in the following publication:
@inproceedings{8594391,
author={F. {Furrer} and T. {Novkovic} and M. {Fehr} and A. {Gawel} and M. {Grinvald} and T. {Sattler} and R. {Siegwart} and J. {Nieto}},
booktitle={2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
title={{Incremental Object Database: Building 3D Models from Multiple Partial Observations}},
year={2018},
pages={6835-6842},
doi={10.1109/IROS.2018.8594391},
ISSN={2153-0866},
month={Oct},
}
If you use Voxblox++ in your research, please cite accordingly.
The code is available under the BSD-3-Clause license.