Abstract
Collecting ground truth-data for real-world applications is a non-trivial but very important task. In order to evaluate new algorithmic approaches or to benchmark system performance, they are inevitable. This is particularly true for robotics applications. In this paper we present our data collection for the biped humanoid robot Nao. Reflective markers were attached to Nao’s body, and the positions and orientation of its body and head were tracked in 6D with an accurate professional vision-based body motion tracking system. While doing so, the data of Nao’s internal state, i.e., the readings of all its servos, the inertial measurement unit, the force receptors plus a camera stream of the robot’s camera were stored for different, typical robotic soccer scenarios in the context of the RoboCup Standard Platform League. These data will be combined in order to compile an accurate ground-truth data set. We describe how the data were recorded, in which format they are stored, and show the usability of the logged data in some first experiments on the recorded data sets. The data sets will be made publicly available for the RoboCup’s Standard Platform League community.
Chapter PDF
Similar content being viewed by others
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
References
Euron - European Robotics Search Network: Survey and inventory of current efforts in comparative robotics research, http://www.robot.uji.es/EURON/en/index.htm
Fontana, G., Matteucci, M., Sorrenti, D.: The RAWSEEDS Proposal for Representation-Independent Benchmarking of SLAM. In: Workshop on Good Experimental Methodologies in Robotics, co-located with Robotics, Science and Systems (2008)
Howard, A., Roy, N.: The Robotics Data Set Repository (Radish) (2003)
Folkesson, J.: Kth slam data sets, http://www.nada.kth.se/~johnf/kthdata/dataset.html
Asuncion, A., Newman, D.: UCI machine learning repository (2007)
Ponce, J.: Datasets for computer vision research, http://www-cvr.ai.uiuc.edu/ponce_grp/data/
Lawrence Berkeley National Laboratory: Berkeley image library, http://www.lbl.gov/image-gallery/image-library.html
Gouaillier, D., Hugel, V., Blazevic, P., Kilner, C., Monceaux, J., Lafourcade, P., Marnier, B., Serre, J., Maisonnier, B.: The nao humanoid: a combination of performance and affordability. CoRR abs/0807.3223 (2008)
Laue, T., de Haas, T.J., Burchardt, A., Graf, C., Röfer, T., Härtl, A., Rieskamp, A.: Efficient and reliable sensor models for humanoid soccer robot self-localization. In: Proceedings of the 4th Workshop on Humanoid Soccer Robots (Humanoid 2009) (2009)
Niemueller, T.: Developing A Behavior Engine for the Fawkes Robot-Control Software and its Adaptation to the Humanoid Platform Nao. Master’s thesis, Knowledge-Based Systems Group, RWTH Aachen University (2009)
Eckel, G., Pirro, D., Sharma, G.K.: Motion-Enabled Live Electronics. In: Proceedings of the 6th Sound and Music Computing Conference, Porto, Portugal (2009)
Rath, C.: Self-localization of a biped robot in the RoboCup domain. Master’s thesis, Institute for Software Technology, Graz University of Technology (2010)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Niemüller, T. et al. (2011). Providing Ground-Truth Data for the Nao Robot Platform. In: Ruiz-del-Solar, J., Chown, E., Plöger, P.G. (eds) RoboCup 2010: Robot Soccer World Cup XIV. RoboCup 2010. Lecture Notes in Computer Science(), vol 6556. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20217-9_12
Download citation
DOI: https://doi.org/10.1007/978-3-642-20217-9_12
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-20216-2
Online ISBN: 978-3-642-20217-9
eBook Packages: Computer ScienceComputer Science (R0)