Ubuntu 14.04+ROS indigo and Ubuntu 16.04+ROS kinetic:
This repository contains maplab, an open, research-oriented visual-inertial mapping framework, written in C++, for processing and manipulating multi-session maps. On the one hand, maplab can be considered as a ready-to-use visual-inertial mapping and localization system. On the other hand, maplab provides the research community with a collection of multi-session mapping tools that include map merging, visual-inertial batch optimization, and loop closure.
Furthermore, it includes an online frontend, ROVIOLI, that can create visual-inertial maps and also track a global drift-free pose within a localization map.
For documentation, tutorials and datasets, please visit the wiki. You can also check out an overview video.
The following articles help you with getting started with maplab and ROVIOLI:
- Installation on Ubuntu 14.04 or 16.04
- Introduction to the maplab framework
- Structure of the framework
- Running ROVIOLI in VIO mode
- Basic console usage
- Console map management
More detailed information can be found in the wiki pages.
The maplab framework has been used as an experimental platform for numerous scientific publications. For a complete list of publications please refer to Research based on maplab.
Please cite the following paper when using maplab for your research:
@article{schneider2018maplab,
title={maplab: An Open Framework for Research in Visual-inertial Mapping and Localization},
author={Schneider, Thomas and Dymczyk, Marcin and Fehr, Marius and Egger, Kevin and
Lynen, Simon and Gilitschenski, Igor and Siegwart, Roland}
year={2018}
}
Certain components of maplab are directly using the code of the following publications:
- Localization:
@inproceedings{lynen2015get, title={Get Out of My Lab: Large-scale, Real-Time Visual-Inertial Localization.}, author={Lynen, Simon and Sattler, Torsten and Bosse, Michael and Hesch, Joel A and Pollefeys, Marc and Siegwart, Roland}, booktitle={Robotics: Science and Systems}, year={2015} }
- ROVIOLI which is composed of ROVIO + maplab for map building and localization:
@article{bloesch2017iterated, title={Iterated extended Kalman filter based visual-inertial odometry using direct photometric feedback}, author={Bloesch, Michael and Burri, Michael and Omari, Sammy and Hutter, Marco and Siegwart, Roland}, journal={The International Journal of Robotics Research}, volume={36}, number={10}, pages={1053--1072}, year={2017}, publisher={SAGE Publications Sage UK: London, England} }
- Thomas Schneider
- Marcin Dymczyk
- Marius Fehr
- Kevin Egger
- Simon Lynen
- Mathias Bürki
- Titus Cieslewski
- Timo Hinzmann
- Mathias Gehrig
For a complete list of contributors, have a look at CONTRIBUTORS.md