Maplab
A Modular and Multi-Modal Mapping Framework
Install / Use
/learn @ethz-asl/MaplabREADME
News
- November 2022: maplab 2.0 initial release with new features and sensors. Paper.
- July 2018: Check out our release candidate with improved localization and lots of new features! Release 1.3.
- May 2018: maplab was presented at ICRA in Brisbane. Paper / Initial Release.
Description
This repository contains maplab 2.0, an open research-oriented mapping framework, written in C++, for multi-session and multi-robot mapping. For the original maplab release from 2018 the source code and documentation is available here.
For documentation, tutorials and datasets, please visit the wiki.
Features
Robust visual-inertial odometry with localization
<img src="https://raw.githubusercontent.com/ethz-asl/maplab/master/docs/pages/readme_images/rovio_stairs.gif" width="400"> <img src="https://raw.githubusercontent.com/ethz-asl/maplab/master/docs/pages/readme_images/rviz_cla_vs.gif" width="400">
Large-scale multisession mapping and optimization
<img src="https://raw.githubusercontent.com/ethz-asl/maplab/master/docs/pages/readme_images/largescale.gif" width="400"> <img src="https://raw.githubusercontent.com/ethz-asl/maplab/master/docs/pages/readme_images/cla.png" width="400">
Multi-robot mapping and online operation
<img src="https://raw.githubusercontent.com/ethz-asl/maplab/master/docs/pages/readme_images/arche.jpg" width="400"> <img src="https://raw.githubusercontent.com/ethz-asl/maplab/master/docs/pages/readme_images/multirobot.gif" width="400">
Dense reconstruction
<img src="https://raw.githubusercontent.com/ethz-asl/maplab/master/docs/pages/readme_images/stereo.png" width="400"> <img src="https://raw.githubusercontent.com/ethz-asl/maplab/master/docs/pages/readme_images/pmvs.png" width="400">
A research platform extensively tested on real robots
<img src="https://raw.githubusercontent.com/ethz-asl/maplab/master/docs/pages/readme_images/topomap.png" width="400"> <img src="https://raw.githubusercontent.com/ethz-asl/maplab/master/docs/pages/readme_images/robots.jpg" width="400">
Installation and getting started
The following articles help you with getting started with maplab and ROVIOLI:
- Installation on Ubuntu 18.04 or 20.04
- Introduction to the maplab framework
- Running ROVIOLI in VIO mode
- Basic console usage
- Console map management
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.
Citing
Please cite the following papers maplab and maplab 2.0 when using our framework for your research:
@article{schneider2018maplab,
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},
volume={3},
number={3},
pages={1418--1425},
year={2018},
doi={10.1109/LRA.2018.2800113}
}
@article{cramariuc2022maplab,
title={{maplab 2.0 – A Modular and Multi-Modal Mapping Framework}},
author={A. Cramariuc and L. Bernreiter and F. Tschopp and M. Fehr and V. Reijgwart and J. Nieto and R. Siegwart and C. Cadena},
journal={IEEE Robotics and Automation Letters},
volume={8},
number={2},
pages={520-527},
year={2023},
doi={10.1109/LRA.2022.3227865}
}
Additional Citations
Certain components of maplab are directly based on other publications.
Credits
- Thomas Schneider
- Marcin Dymczyk
- Marius Fehr
- Kevin Egger
- Simon Lynen
- Mathias Bürki
- Titus Cieslewski
- Timo Hinzmann
- Mathias Gehrig
- Florian Tschopp
- Andrei Cramariuc
- Lukas Bernreiter
For a complete list of contributors, have a look at CONTRIBUTORS.md
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