Skip to main content
SpringerLink
Log in

DCCD: Distributed N-Body Rigid Continuous Collision Detection for Large-Scale Virtual Environments

  • Research Article - Computer Engineering and Computer Science
  • Published:
Arabian Journal for Science and Engineering Aims and scope Submit manuscript

Abstract

Continuous collision detection (CCD) is a process to interpolate the trajectory of polygons and detect collisions between successive time steps. However, this process is time-consuming, especially for a large number of moving polygons. In this paper, we present a parallel CCD algorithm, which aims to accelerate N-body rigid CCD culling by distributing the load across a distributed-memory system. This algorithm is particularly suitable for large-scale distributed simulations. Experimental results, based on a message passing interface implementation, demonstrate that our approach is more computationally efficient than existing sequential CCD approaches.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Perumalla, K.; Fujimoto, R.; McLean, T.; Riley, G.: Experiences applying parallel and interoperable network simulation techniques in on-line simulations of military networks. In: Proceedings of the 16th Workshop on Parallel and Distributed Simulation (2002)

  2. Smed, J.; Kaukoranta, T.; Hakonen, H.: A Review on Networking and Multiplayer Computer Games. Technical Report 454, Turku Centre for Computer Science (April 2002)

  3. Fujimoto, R.M.: Parallel and Distributed Simulation Systems. Wiley, London (2000)

    Google Scholar 

  4. Tang, M.; Manocha, D.; Otaduy, M.A.; Tong, R.: Continuous penalty forces. ACM Trans. Graph. 31(4), 107:1–107:9 (2012)

    Article  Google Scholar 

  5. Lee, J.; Kwon, O.; Zhang, L.; Yoon, S.E.: A selective retraction-based RRT planner for various environments. IEEE Trans. Robot. 30(4), 1002–1011 (2014)

    Article  Google Scholar 

  6. Du, P.; Zhao, J.Y.; Pan, W.B.; Wang, Y.G.: GPU accelerated real-time collision handling in virtual disassembly. J. Comput. Sci. Technol. 30(3), 511–518 (2015)

    Article  Google Scholar 

  7. Tang, M.; Curtis, S.; Yoon, S. E.; Manocha, D.: Interactive continuous collision detection between deformable models using connectivity-based culling. In: Proceedings of the 2008 ACM Symposium on Solid and Physical Modeling, pp. 25–36. ACM Press, Stony Brook (2008)

  8. Tang, M.; Manocha, D.; Tong, R.F.: MCCD: multi-core collision detection between deformable models using front-based decomposition. Graph. Models 72, 7–23 (2010)

    Article  Google Scholar 

  9. Tang, M.; Manocha, D.; Lin, J.; Tong, R. F.: Collision-streams: fast GPU-based collision detection for deformable models. In: Proceedings of the ACM SIGGRAPH Symposium on Interactive 3D Graphics and Games, pp. 63–70. ACM Press, New York (2011)

  10. Wong, S.K.; Lin, W.C.; Hung, C.H.; Huang, Y.J.; Lii, S.Y.: Radial view based culling for continuous self-collision detection of skeletal models. ACM Trans. Graph. 32(4), 114:1–114:10 (2013)

    Article  MATH  Google Scholar 

  11. Bradshaw, G.; O’Sullivan, C.: Adaptive medial-axis approximation for sphere-tree construction. ACM Trans. Graph. 23, 1–26 (2004)

    Article  Google Scholar 

  12. Bergen, G.V.D.: Efficient collision detection of complex deformable models using AABB trees. J. Graph. Tools 2, 1–14 (1998)

    Article  MATH  Google Scholar 

  13. Klosowski, J.; Held, M.; Mitchell, J.; Sowizral, H.; Zikan, K.: Efficient collision detection using bounding volume hierarchies of k-dops. IEEE Trans. Vis. Comput. Graph. 4, 21–37 (1998)

    Article  Google Scholar 

  14. Curtis, S.; Tamstorf, R.; Manocha, D.: Fast collision detection for deformable models using representative-triangles. In: Proceedings of the ACM SIGGRAPH Symposium on Interactive 3D Graphics and Games, pp. 61–69. ACM Press, London (2008)

  15. Tang, M.; Manocha, D.; Yoon, S.E.; Du, P.; Heo, J.P.; Tong, R.F.: VolCCD: fast continuous collision culling between deforming volume meshes. ACM Trans. Graph. 30, 111–125 (2011)

    Article  Google Scholar 

  16. Tang, M.; Manocha, D.; Tong, R. F.: Fast continuous collision detection using deforming non-penetration filters. In: Proceedings of the ACM SIGGRAPH Symposium on Interactive 3D Graphics and Games, pp. 7–14. ACM Press, London (2010)

  17. Du, P.; Tang, M.; Tong, R.F.: Fast continuous collision culling with deforming non-collinear filters. Comput. Anim. Virtual Worlds 23(6–8), 375–383 (2012)

    Article  Google Scholar 

  18. Cohen, J.; Lin, M.; Manocha, D.; Ponamgi, M.: I-collide: An interactive and exact collision detection system for large-scale environments. In: I3D (1995)

  19. Liu, F.;  harada, T., Lee, Y., Kim, Y. J.: Real-time collision culling of a million bodies on graphics processing units. In: SIGGRAPH ASIA (2010)

  20. Kim, D.; Heo, J.P.; Huh, J.; Kim, J.; Yoon, S.E.: HPCCD: hybrid parallel continuous collision detection using CPUs and GPUs. Comput. Graph. Forum 28, 1791–1800 (2009)

    Article  Google Scholar 

  21. Tang, M.; Zhao, J.-Y.; Tong, R.-F.; Manocha, D.: GPU accelerated convex hull computation. Comput. Graph. 36(5), 498–506 (2012)

    Article  Google Scholar 

  22. Lawlor, O. S.; Kalée, L. V.: A voxel-based parallel collision detection algorithm. In: ICS (2002)

  23. Samet, H.: Foundations of Multidimensional and Metric Data Structures. Kaufmann, Los Altos (2006)

    MATH  Google Scholar 

  24. Open MPI: A high performance message passing library. http://www.open-mpi.com/ (2015)

  25. Liu, E. S.: On the scalability of agent-based modeling for medical nanorobotics. In: Proceedings of Winter Simulation Conference (WSC) (2015)

Download references

Author information

Authors and Affiliations

  1. School of Media and Design, Hangzhou Dianzi University, Hangzhou, 310018, China

    Peng Du, Weijuan Cao & Yigang Wang

  2. University of Texas School of Biomedical Informatics, Houston, TX, 77030, USA

    Jieyi Zhao

Authors
  1. Peng Du
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jieyi Zhao
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Weijuan Cao
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Yigang Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Yigang Wang.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Du, P., Zhao, J., Cao, W. et al. DCCD: Distributed N-Body Rigid Continuous Collision Detection for Large-Scale Virtual Environments. Arab J Sci Eng 42, 3141–3147 (2017). https://doi.org/10.1007/s13369-016-2411-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s13369-016-2411-0

Keywords

Search

Navigation