Advertisement

GPU Calculated Camera Collisions Detection within a Dynamic Environment

  • Adam Wojciechowski
  • Grzegorz Wróblewski
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6375)

Abstract

Existing collision detection methods usually need long pre-calculation stage or difficult, time-consuming real-time computation. Moreover, their effectiveness considerably decreases with the growth of the complexity of the scene. Especially dynamic scenes with moving objects require the necessity of each frame collisions recalculation due to changeable objects’ position and orientation. So far seemingly promising solutions supported by potential fields do not introduce satisfactory functionality as they are mainly devoted to static scenes with one predefined goal. This paper introduces a method which offers a new dynamic GPU supported potential field construction which lets the camera collide with both dynamic and static objects. Additionally, the proposed method does not need pre-calculation stage and provides an almost scene-complexity independent solution. The presented method is based on an arbfp1 shader solution, which means that most contemporary graphics cards can operate it without constraints

Keywords

collision detection GPGPU potential field navigation dynamic scene 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Beckhaus, S., Ritter, F., Strothotte, T.: CubicalPath - Dynamic Potential Fields for Guided Exploration in Virtual Environments. In: PG 2000. IEEE, Los Alamitos (2000)Google Scholar
  2. 2.
    Beckhaus, S.: Dynamic Potential Fields for Guided Exploration in Virtual Environments. PhD thesis, Otto-von-Gueicke-Universitat Magdeburg (2002)Google Scholar
  3. 3.
    Dulęba, I.: Metody i algorytmy planowania ruchu robot”ow mobilnych i manipulacyjnych. Akademicka Oficyna Wydawnicza Exit (2004)Google Scholar
  4. 4.
    Khatib, O.: Real-time obstacle avoidance for manipulators and mobile robots. International Journal of Mobile Research 5(1), 90–99 (1986)MathSciNetGoogle Scholar
  5. 5.
    Khatib, M., Chatila, R.: An Extended Potential Field Approach for Mobile Robot Sensor-based Motions. In: Intl. Conf. on Intelligent Autonomous Systems, IAS’4 (1995)Google Scholar
  6. 6.
    Latombe, J.C.: Robot Motion Planning. Kluwer Academic Publishers, Dordrecht (1991)Google Scholar
  7. 7.
    Li, T.Y., Chou, H.C.: Improving Navigation Efficiency with Artificial Force Fields. In: Proceedings of 14th IPPR Conference on CVGIP, Taiwan (2001)Google Scholar
  8. 8.
    Li, T.Y., Hsu, S.W.: An Intelligent 3D User Interface Adapting to User Control Behaviours. In: Proc. of the 9th Int. Conf. on Int. UI, Madeira, Portugal, pp. 184–190 (2004)Google Scholar
  9. 9.
    Murphy, R.R.: Introduction to AI Robotics. MIT Press, Cambridge (2000)Google Scholar
  10. 10.
    Szajerman, D., Pietruszka, M.: Real-time ice visualization on the GPU. Journal of Applied Computer Science 16(2), 89–106 (2008)Google Scholar
  11. 11.
    Watt, A., Policarpo, F.: 3D Games. Real-time Rendering and Software Technology. Addison-Wesley, Reading (2002)Google Scholar
  12. 12.
    Wojciechowski, A.: Wspomaganie dynamiki procesu nawigacji w eksploracyjnym ”srodowisku wirtualnym. PhD Thesis, Technical University of Lodz (2005)Google Scholar
  13. 13.
    Wojciechowski, A.: Potential field based camera collisions detection in a static 3D environment. Machine Graphics and Vision 15(3/4), 665–672 (2006)Google Scholar
  14. 14.
    Wojciechowski, A.: Potential field based camera collisions detection within dynamically moving 3D objects. LNCS. Springer, Heidelberg (2009)Google Scholar
  15. 15.
    Xiao, D., Hubbold, R.: Navigation Guided by Artificial Force Fields. In: Proceedings of CHI 1998, Los Angeles, USA (1998)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Adam Wojciechowski
    • 1
  • Grzegorz Wróblewski
    • 1
  1. 1.Institute of Computer ScienceTechnical University of ŁódźŁódźPoland

Personalised recommendations