Skip to main content
SpringerLink
Log in

Semantic Simulation Engine for Supervision of Mobile Robotic System

  • Conference paper
Computational Collective Intelligence. Technologies and Applications (ICCCI 2011)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6923))

Included in the following conference series:

Abstract

In the paper semantic simulation engine for supervision of mobile robotic system is described. Semantic simulation engine provides tools to implement mobile robot simulation based on real data delivered by robot observations in INDOOR environment. The supervision of real objects such as robots is performed by association with its virtual representation in the simulation, therefore events such as object intersection, robot pitch roll are defined. Semantic simulation engine is composed of data registration modules, semantic entities identification modules and semantic simulation module. The data registration modules delivers 3D point clouds aligned with ICP (Iterative Closest Point) algorithm. Semantic entities identification modules provide implementation of methods for obtaining semantic entities from robot observations. Semantic simulation module executes rigid body simulation with predefined simulation events. The simulation can be integrated with real part of the system with an assumption of robust localization of real entities.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Asada, M., Shirai, Y.: Building a world model for a mobile robot using dynamic semantic constraints. In: Proc. 11 th International Joint Conference on Artificial Intelligence, pp. 1629–1634 (1989)

    Google Scholar 

  2. Nüchter, A., Wulf, O., Lingemann, K., Hertzberg, J., Wagner, B., Surmann, H.: 3d mapping with semantic knowledge. In: Robocup International Symposium, pp. 335–346 (2005)

    Google Scholar 

  3. Nüchter, A., Hertzberg, J.: Towards semantic maps for mobile robots. Robot. Auton. Syst. 56(11), 915–926 (2008)

    Article  Google Scholar 

  4. Grau, O.: A scene analysis system for the generation of 3-d models. In: NRC 1997: Proceedings of the International Conference on Recent Advances in 3-D Digital Imaging and Modeling, p. 221 (1997)

    Google Scholar 

  5. Nüchter, A., Surmann, H., Lingemann, K., Hertzberg, J.: Semantic scene analysis of scanned 3d indoor environments. In: Proceedings of the Eighth International Fall Workshop on Vision, Modeling, and Visualization, VMV 2003 (2003)

    Google Scholar 

  6. Cantzler, H., Fisher, R.B., Devy, M.: Quality enhancement of reconstructed 3d models using coplanarity and constraints. In: Proceedings of the 24th DAGM Symposium on Pattern Recognition, pp. 34–41 (2002)

    Google Scholar 

  7. Fischler, M.A., Bolles, R.: Random sample consensus. a paradigm for model fitting with apphcahons to image analysm and automated cartography. In: Baurnann, L.S. (ed.) Proc. 1980 Image Understandtng Workshop (College Park, Md., Apr i980), Scmnce Apphcatlons, McLean, Va, pp. 71–88 (1980)

    Google Scholar 

  8. Eich, M., Dabrowska, M., Kirchner, F.: Semantic labeling: Classification of 3d entities based on spatial feature descriptors. In: IEEE International Conference on Robotics and Automation (ICRA 2010), Anchorage, Alaska (May 3, 2010)

    Google Scholar 

  9. Vaskevicius, N., Birk, A., Pathak, K., Poppinga, J.: Fast detection of polygons in 3d point clouds from noise-prone range sensors. In: IEEE International Workshop on Safety, Security and Rescue Robotics, SSRR, pp. 1–6 (2007)

    Google Scholar 

  10. Andreasson, H., Triebel, R., Burgard, W.: Improving plane extraction from 3d data by fusing laser data and vision. In: Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 2656–2661 (2005)

    Google Scholar 

  11. Nüchter, A., Surmann, H., Hertzberg, J.: Automatic model refinement for 3D reconstruction with mobile robots, In: Fourth International Conference on 3-D Digital Imaging and Modeling 3DIM 2003, p. 394 (2003)

    Google Scholar 

  12. Davison, A., Cid, Y.G., Kita, N.: Real-time 3D SLAM with wide-angle vision. In: Proc. IFAC Symposium on Intelligent Autonomous Vehicles, Lisbon (2004)

    Google Scholar 

  13. Castle, R.O., Klein, G., Murray, D.W.: Combining monoslam with object recognition for scene augmentation using a wearable camera, vol. 28(11), pp. 1548–1556 (2010)

    Google Scholar 

  14. Thrun, S., Burgard, W., Fo, D.: A real-time algorithm for mobile robot mapping with applications to multi-robot and 3d mapping. In: ICRA, pp. 321–328 (2000)

    Google Scholar 

  15. Magnusson, M., Andreasson, H., Nüchter, A., Lilienthal, A.J.: Automatic appearance-based loop detection from 3D laser data using the normal distributions transform. Journal of Field Robotics 26(11-12), 892–914 (2009)

    Article  MATH  Google Scholar 

  16. Magnusson, M., Duckett, T., Lilienthal, A.J.: 3d scan registration for autonomous mining vehicles. Journal of Field Robotics 24(10), 803–827 (2007)

    Article  Google Scholar 

  17. Andreasson, H., Lilienthal, A.J.: Vision aided 3d laser based registration. In: Proceedings of the European Conference on Mobile Robots (ECMR), pp. 192–197 (2007)

    Google Scholar 

  18. Besl, P.J., Mckay, H.D.: A method for registration of 3-d shapes. IEEE Transactions on Pattern Analysis and Machine Intelligence 14(2), 239–256 (1992)

    Article  Google Scholar 

  19. Magnusson, M., Nüchter, A., Lörken, C., Lilienthal, A.J., Hertzberg, J.: Evaluation of 3d registration reliability and speed - a comparison of icp and ndt. In: Proc. IEEE Int. Conf. on Robotics and Automation, pp. 3907–3912 (2009)

    Google Scholar 

  20. Rusu, R.B., Marton, Z.C., Blodow, N., Dolha, M., Beetz, M.: Towards 3d point cloud based object maps for household environments. Robot. Auton. Syst. 56(11), 927–941 (2008)

    Article  Google Scholar 

  21. Craighead, J., Murphy, R., Burke, J., Goldiez, B.: A survey of commercial and open source unmanned vehicle simulators. In: Proceedings of ICRA (2007)

    Google Scholar 

  22. Boeing, A., Bräunl, T.: Evaluation of real-time physics simulation systems. In: GRAPHITE 2007: Proceedings of the 5th International Conference on Computer Graphics and Interactive Techniques in Australia and Southeast Asia, pp. 281–288 (2007)

    Google Scholar 

  23. Wang, J., Lewis, M., Gennari, J.: Usar: A game-based simulation for teleoperation. In: Proceedings of the 47th Annual Meeting of the Human Factors and Ergonomics Society, Denver, CO (October 13-17, 2003)

    Google Scholar 

  24. Greggio, N., Silvestri, G., Menegatti, E., Pagello, E.: A realistic simulation of a humanoid robot in usarsim. In: Proceeding of the 4th International Symposium on Mechatronics and its Applications (ISMA 2007), Sharjah, U.A.E (2007)

    Google Scholar 

  25. Rusu, R.B., Maldonado, A., Beetz, M., Systems, I.A., München, T.U.: Extending player/stage/gazebo towards cognitive robots acting in ubiquitous sensor-equipped environments. In: IEEE International Conference on Robotics and Automation (ICRA) Workshop for Network Robot System (April 14, 2007)

    Google Scholar 

  26. Hohl, L., Tellez, R., Michel, O., Ijspeert, A.J.: Aibo and Webots: Simulation, Wireless Remote Control and Controller Transfer. Robotics and Autonomous Systems 54(6), 472–485 (2006)

    Article  Google Scholar 

  27. Petrinić, T., Ivanjko, E., Petrović, I.: Amorsim – a mobile robot simulator for matlab. In: Proceedings of 15th International Workshop on Robotics in Alpe-Adria-Danube Region, Balatonfüred, Hungary (June 15-17, 2006)

    Google Scholar 

  28. Buckhaults, C.: Increasing computer science participation in the first robotics competition with robot simulation. In: ACM-SE 47: Proceedings of the 47th Annual Southeast Regional Conference, pp. 1–4 (2009)

    Google Scholar 

  29. Craighead, J., Murphy, R., Burke, J., Goldiez, B.: A robot simulator classification system for hri. In: Proceedings of the 2007 International Symposium on Collaborative Technologies and Systems, pp. 93–98 (2007)

    Google Scholar 

  30. Craighead, J.: Distributed, game-based, intelligent tutoring systems – the next step in computer based training? In: Proceedings of the International Symposium on Collaborative Technologies and Systems (2008)

    Google Scholar 

  31. Huber, D., Hebert, M.: Fully automatic registration of multiple 3d data sets. Image and Vision Computing 21(1), 637–650 (2003)

    Article  Google Scholar 

  32. Fitzgibbon, A.W.: Robust registration of 2d and 3d point sets. In: British Machine Vision Conference, pp. 411–420 (2001)

    Google Scholar 

  33. Magnusson, M., Duckett, T.: A comparison of 3d registration algorithms for autonomous underground mining vehicles. In: Proc. ECMR, pp. 86–91 (2005)

    Google Scholar 

  34. Nuchter, A., Lingemann, K., Hertzberg, J.: Cached k-d tree search for icp algorithms. In: Proceedings of the Sixth International Conference on 3-D Digital Imaging and Modeling, pp. 419–426 (2007)

    Google Scholar 

  35. Rusinkiewicz, S., Levoy, M.: Efficient variants of the ICP algorithm. In: Third International Conference on 3D Digital Imaging and Modeling (3DIM) (2001)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Institute of Automation and Robotics, Warsaw, Poland

    Janusz Bedkowski & Andrzej Masłowski

  2. Institute of Mathematical Machines, Warsaw, Poland

    Janusz Bedkowski & Andrzej Masłowski

Authors
  1. Janusz Bedkowski
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Andrzej Masłowski
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Gdynia Maritime University, Morska 81-87, 81-225, Gdynia, Poland

    Piotr Jędrzejowicz

  2. Wroclaw University of Technology, Wyb. Wyspianskiego 27, 50-370, Wroclaw, Poland

    Ngoc Thanh Nguyen

  3. University of Information Technology Vietnam, Km 20, Xa lo Ha Noi, Linh Trung, Thu Duc, 848, HCM City, Vietnam

    Kiem Hoang

Rights and permissions

Reprints and permissions

Copyright information

© 2011 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Bedkowski, J., Masłowski, A. (2011). Semantic Simulation Engine for Supervision of Mobile Robotic System. In: Jędrzejowicz, P., Nguyen, N.T., Hoang, K. (eds) Computational Collective Intelligence. Technologies and Applications. ICCCI 2011. Lecture Notes in Computer Science(), vol 6923. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23938-0_14

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-23938-0_14

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-23937-3

  • Online ISBN: 978-3-642-23938-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation