Pioneer

Image Database for Vision-Based Self-Localization in Mobile Robotics

Image datasets recorded with an optical camera onboard a Pioneer robot. Each dataset represents a path along the corridors of the Facultad de Informática de San Sebastián building and is composed of six different walks along the same path. Along with each walk, a .txt file with the reference odometry positions is provided.
Due storage limitations, only the low resolution (79x61) images are available for download. Higher resolution images (314x242) could be provided upon request.

• First sample path, low resolution (Download, 22MB).
  • Matlab .mat file.
• Second sample path, low resolution (Download, 33MB).
• Third sample path, low resolution (Download, 29MB).
• Fourth sample path, low resolution (Download, 24MB).
• Fifth sample path, low resolution (Download, 21MB).

Samples

Some sample images form the first path.

• Sample images form the first path.
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Citation

If you are using these datasets for your scientific research, please reference it as follows:

   Image Database for Vision-Based Self-Localization in Mobile Robotics.
   Computational Intelligence Group, University of the Basque Country, San Sebastián, Spain. 
   http://www.ehu.es/ccwintco/index.php/Pioneer

Or you can use the following bibtex code:

\bibitem{idb} Image {D}atabase for {V}ision-{B}ased {S}elf-{L}ocalization in {M}obile {R}obotics,
available at {\tt http://www.ehu.es/ccwintco/index.php/Pioneer},
Computational Intelligence Group, University of the Basque Country, San Sebasti\'an, Spain.

References

• Peter Sussner, Estevão L. Esmi, Ivan Villaverde and Manuel Graña. The Kosko Subsethood FAM: Mathematical Background, Properties, and Some Experimental Results in Computer Vision. Journal of Mathematical Imaging and Vision (accepted minor revisions)
• Manuel Graña, Ivan Villaverde, Jose Manuel Lopez-Guede and Borja Fernadez-Gauna, Lattice Independent Component Analysis for Appearance Based Mobile Robot Localization. Neural Computing and Applications, Springer (submitted).
• Ivan Villaverde, Borja Fernandez-Gauna and Ekaitz Zulueta, Lattice Independent Component Analysis for mobile robot localization. In E. Corchado et al. (Eds.), The 5th International Conference on Hybrid Artificial Intelligence Systems (HAIS 2010), Part II, LNAI vol. 6077, pp. 335-342. Springer, Heidelberg, 2010. (ISBN 978-3-642-13802-7). DOI
• Ivan Villaverde, On Computational Intelligence Tools for Vision Based Navigation of Mobile Robots, PhD Thesis, University of the Basque Country, 2009. ISBN 978-84-9860-340-8 (Donwnload PDF)
• Ivan Villaverde, Alicia D'Anjou, Manuel Graña. Morphological Neutal Networks and Vision Based Simultaneous Localization and Maping. Integrated Computer-Aided Engineering. 14(4):355-363. IOS Press (2007). On-line
• Ivan Villaverde, Manuel Graña, Jose Luis Jiménez, Lattice Independence and Vision Based Mobile Robot Navigation. Knowledge-Based Intelligent Information and Engineering Systems, KES 2007, Bruno Apolloni, Robert J. Howlett, and Lakhmi Jain (Eds.) LNAI 4693, pp. 1196-1203 Springer-Verlag, Heidelberg, 2007. ISBN 978-3-540-74826-7. DOI
• Ivan Villaverde, Manuel Graña, Alicia d’Anjou, Morphological Independence for Landmark Detection in Vision Based SLAM. F. Sandoval, A. Prieto, J. Cabestany, M. Graña (Eds.) Proc. of IWANN 2007, Lecture Notes in Computer Science, Vol. 4507, pp. 847-854. Springer-Verlag Heidelberg, 2007. ISBN 3-540-73006-0. DOI
• Manuel Graña, Ivan Villaverde, Ramon Moreno, and Francisco X. Albizuri, Convex Coordinates From Lattice Independent Sets for Visual Pattern Recognition, Vassilis G. Kaburlasos, Gerhard X. Ritter (eds.) Computational Intelligence Based on Lattice Theory, Cap. 6, pp. 99-126. Springer, 2007. ISBN 978-3-540-72686-9. DOI
• Ivan Villaverde, Manuel Graña, Alicia D'Anjou, Morphological Neural Networks and Vision Based Mobile Robot Navigation. Proc. of ICANN 2006 in Lecture Notes in Computer Science, Vol. 4131, pp. 878-887, Springer, Heidelberg, 2006. ISBN 3-540-38625-4. DOI
• I. Villaverde, M. Graña and A. D’Anjou, Morphological Neural Networks for Localization and Mapping. Proceedings of the IEEE International Conference on Computational Intelligence for Measurement Systems and Applications (CIMSA’06), IEEE Press, ISBN 1-4244-0245-X, pp. 9-14. (2006). DOI