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Ubuntu 14.04+ROS indigo and Ubuntu 16.04+ROS kinetic: Build Status


  • May 2018: maplab was presented at ICRA in Brisbane. (paper)
  • March 2018: Check out our release candidate with improved localization and lots of new features! PR


This repository contains maplab, an open, research-oriented visual-inertial mapping framework, written in C++, for creating, 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.

Please also check out our video:


Robust visual-inertial odometry with localization

Large-scale multisession mapping and optimization

Dense reconstruction

A research platform extensively tested on real robots

Installation and getting started

The following articles help you with getting started with maplab and ROVIOLI:

More detailed information can be found in the wiki pages.

Research Results

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 or ROVIOLI for your research:

  title={maplab: An Open Framework for Research in Visual-inertial Mapping and Localization},
  author={T. Schneider and M. T. Dymczyk and M. Fehr and K. Egger and S. Lynen and I. Gilitschenski and R. Siegwart},
  journal={IEEE Robotics and Automation Letters},

Additional Citations

Certain components of maplab are directly using the code of the following publications:

  • Localization:
      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},
  • ROVIOLI which is composed of ROVIO + maplab for map building and localization:
      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},
      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