ATOM Calibration

A Calibration Framework using the
Atomic Transformations Optimization Method

ATOM is a set of calibration tools for multi-sensor, multi-modal, robotic systems, based on the optimization of atomic transformations as provided by a ROS based robot description. Moreover, ATOM provides several scripts to facilitate all the steps of a calibration procedure.

For instructions on how to install and use, check the documentation:

https://lardemua.github.io/atom_documentation/

Also, you can take a look at the ATOM youtube playlist.

Support

If this work is helpful for you please cite our paper:

• Oliveira, M., E. Pedrosa, A. Aguiar, D. Rato, F. Santos, P. Dias, V. Santos, ATOM: A general calibration framework for multi-modal, multi-sensor systems, Expert Systems with Applications (2022), 118000, ISSN 0957-4174, https://doi.org/10.1016/j.eswa.2022.118000. Bibtex.
  

or any other that is more adequate:

• Gomes, M. M. Oliveira, V. Santos, ATOM Calibration Framework: Interaction and Visualization Functionalities, Sensors (2023), 23, 936. https://doi.org/10.3390/s23020936. Bibtex.
  

• Rato, D., M. Oliveira, V. Santos, M. Gomes, A. Sappa, A sensor-to-pattern calibration framework for multi-modal industrial collaborative cells, Journal of Manufacturing Systems (2022), Volume 64, Pages 497-507, ISSN 0278-6125, https://doi.org/10.1016/j.jmsy.2022.07.006. Bibtex.
  

• Pedrosa, E., M. Oliveira, N. Lau, and V. Santos, A General Approach to Hand–Eye Calibration Through the Optimization of Atomic Transformations, IEEE Transactions on Robotics (2021) pp. 1–15, DOI: https://doi.org/10.1109/TRO.2021.3062306, 2021. Bibtex.
  

• Aguiar, A., M. Oliveira, E. Pedrosa, and F. Santos, A Camera to LiDAR calibration approach through the Optimization of Atomic Transformations, Expert Systems with Applications (2021) p. 114894, ISSN: 0957-4174, DOI: https://doi.org/10.1016/j.eswa.2021.114894, 2021. Bibtex.
  

• Oliveira, M., A. Castro, T. Madeira, E. Pedrosa, P. Dias, and V. Santos, A ROS framework for the extrinsic calibration of intelligent vehicles: A multi-sensor, multi-modal approach, Robotics and Autonomous Systems (2020) p. 103558, ISSN: 0921-8890, DOI: https://doi.org/10.1016/j.robot.2020.103558, 2020. Bibtex.
  

Contributors

• Miguel Riem Oliveira - University of Aveiro
• Afonso Castro - University of Aveiro
• Eurico Pedrosa - University of Aveiro
• Tiago Madeira - University of Aveiro
• André Aguiar - INESC TEC
• Daniela Rato - University of Aveiro
• Manuel Gomes - University of Aveiro

Maintainers

• Miguel Riem Oliveira - University of Aveiro
• Manuel Gomes - University of Aveiro