Server-Sided Automatic Map Transformation in RoboEarth

  • Alexander Perzylo
  • Björn Schießle
  • Kai Häussermann
  • Oliver Zweigle
  • Paul Levi
  • Alois Knoll
Conference paper
Part of the Informatik aktuell book series (INFORMAT)


RoboEarth aims at providing a distributed cloud-based web platform from robots for robots that is publicly accessible and enables robots to autonomously share knowledge among each other and to generate new knowledge from previously stored data. As a result robots don’t have to gain the same knowledge over and over again, but can build upon it right from the start. Currently, shareable data are abstract task descriptions, object models and environment maps. In this paper we describe RoboEarth’s approach to automatically and transparently generate 2D maps for localization and navigation, which are extracted from shared 3D maps and suited for a specific robot configuration. The parameters of the map generation process get inferred from a robot’s semantic self-description. Using RoboEarth for knowledge generation enables simple platforms with low computational power to execute complex tasks in complex environments. Furthermore the approach effectively simplifies the time consuming process of generating new maps every time a new robot platform with different specifications is used.



The research leading to these results has received funding from the European Union Seventh Framework Programme FP7/2007–2013 under grant agreement number 248942 RoboEarth


  1. Arumugam, R., Enti, V.R., Bingbing, L., Xiaojun, W., Baskaran, K., Kong, F.F., Kumar, A.S., Meng, K.D., Kit, G.W.: Davinci: A cloud computing framework for service robots. In: IEEE International Conference on Robotics and Automation (ICRA), pp. 3084–3089, May (2010)Google Scholar
  2. Allen, P., Stamos, I., Gueorguiev, A., Gold, E., Blaer, P.: Avenue: Automated site modeling in urban environments. In: Proceedings of Third International Conference on 3-D Digital Imaging and Modeling, pp. 357–364, IEEE (2001)Google Scholar
  3. A-star Social Robotics Laboratory, Singapore (asoro).
  4. Bellutta, P., Manduchi, R., Matthies, L., Owens, K., Rankin, A.: Terrain perception for demo III. In: Proceedings of the Intelligent Vehicles Symposium IV, IEEE, pp. 326–331. IEEE (2000)Google Scholar
  5. Brenneke, C., Wulf, O., Wagner, B.: Using 3d laser range data for slam in outdoor environments. In: Proceedings of Intelligent Robots and Systems (IROS 2003), IEEE/RSJ International Conference on, vol. 1, pp. 188–193. IEEE (2003)Google Scholar
  6. Broeskstra, J., Kampman, A.: Serql: A second generation rdf query language. In: SWAD-Europe Workshop on Semantic Web Storage and Retrieval, pp. 13–14 (2003)Google Scholar
  7. Chang, F., Dean, J., Ghemawat, S., Hsieh, W.C., Wallach, D.A., Burrows, M., Chandra, T., Fikes, A., Gruber, R.E.: Bigtable: A distributed storage system for structured data. In: Seventh Symposium on Operating System Design and Implementation (OSDI’06) (2006)Google Scholar
  8. Crockford, D., RFC4627-The application/json Media Type for JavaScript Object Notation (JSON)., July 2006
  9. Dean, J., Ghemawat, S.: Mapreduce: Simplified data processing on large clusters. In: Sixth Symposium on Operating System Design and Implementation (OSDI’04) (2004)Google Scholar
  10. Eindhoven University of Technology Control Systems Technology Group. AMIGO specifications. Accessed 10 March 2012
  11. Fielding, R.T.: Architectural styles and the design of network-based software architectures. Ph.D. thesis, University of California, Irvine (2000)Google Scholar
  12. Garage, W.: XML robot description format (URDF). Accessed 10 March 2012
  13. Hebert, M., Deans, M., Huber, D., Nabbe, B., Vandapel, N.: Progress in 3-d mapping and localization. In: International Symposium on Intelligent Robotic Systems, pp. 145–154 (2001)Google Scholar
  14. Kunze, L., Roehm, T., Beetz, M.: Towards semantic robot description languages. In: IEEE International Conference on Robotics and Automation (ICRA), Shanghai, China, 9–13 May 2011Google Scholar
  15. Lacroix, S., Mallet, A., Bonnafous, D., Bauzil, G., Fleury, S., Herrb, M., Chatila, R.: Autonomous rover navigation on unknown terrains: functions and integration. The Int. J. Rob. Res. 21(10–11), 917–942 (2002)CrossRefGoogle Scholar
  16. Murthy, A.C., Douglas, C., Cutting, D., Das, D., Borthakur, D., Collins, E., Soztutar, E., Kuang, H., Homan, J., Konar, M., Daley, N., O’Malley, O., Hunt, P., Angadi, R., Agarwal, S., Shvachko, K., Stack, M., (Nicholas) Sze, T.W., Lipcon, T., White, T., Shao, Z.: Apache Hadoop, a framework for reliable, scalable and distributed computing.
  17. Sesame (2007)Google Scholar
  18. Quigley, M., Gerkey, B., Conley, K., Faust, J., Foote, T., Leibs, J., Berger, E., Wheeler, R., Ng, A.: ROS: an open-source Robot Operating System. ICRA Workshop on Open Source Software, In (2009)Google Scholar
  19. Schießle, B., Häussermann, K., Zweigle, O.: Deliverable D6.1: Complete specification of the RoboEarth platform. Technical report, December 1, 2010.
  20. Tenorth, M.: SRDL2 Tutorial. Accessed 10 March 2012
  21. Tenorth, M., Beetz, M.: Deliverable D5.2: The RoboEarth Language-Language Specification. Technical report, August 02, 2010.
  22. Tenorth, M., Perzylo, A., Lafrenz, R., Beetz, M.: The RoboEarth language: Representing and Exchanging Knowledge about Actions, Objects, and Environments. In: IEEE International Conference on Robotics and Automation (ICRA), Saint Paul, USA, 2012. Accepted for publicationGoogle Scholar
  23. Thrun, S.: Robotic mapping: a survey. In: Exploring artificial intelligence in the new millennium, pp. 1–35 (2002)Google Scholar
  24. Waibel, M., Beetz, M., Civera, J., D’Andrea, R., Elfring, J., Galvez-Lopez, D., Haussermann, K., Janssen, R., Montiel, J.M.M., Perzylo, A., et al.: Roboearth. IEEE Rob. Autom. Mag. 18(2), 69–82 (2011)Google Scholar
  25. W3C OWL Working Group. OWL 2 Web Ontology Language Document Overview. W3C recommendation, W3C, October 2009.
  26. Wurm, K.M., Hornung, A., Bennewitz, M., Stachniss, C., Burgard, W.: OctoMap: A probabilistic, flexible, and compact 3D map representation for robotic systems. In: Proceedings of the ICRA 2010 Workshop on Best Practice in 3D Perception and Modeling for Mobile Manipulation, Anchorage, AK, USA, May 2010. Software available at
  27. Zweigle, O., van de Molengraft, R., D’Andrea, R., Häussermann, K.: RoboEarth: connecting robots worldwide. In: Proceedings of the International Conference on Interaction Sciences: Information Technology, Culture and Human, pp. 184–191. ACM (2009)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Alexander Perzylo
    • 1
  • Björn Schießle
    • 2
  • Kai Häussermann
    • 2
  • Oliver Zweigle
    • 2
  • Paul Levi
    • 2
  • Alois Knoll
    • 1
  1. 1.Department of Robotics and Embedded SystemsTechnische Universität MünchenGarching bei MünchenGermany
  2. 2.Department of Image UnderstandingUniversität StuttgartStuttgartGermany

Personalised recommendations