Skip to main content
SpringerLink
Log in

An Adaptive Stochastic Collision Detection Between Deformable Objects Using Particle Swarm Optimization

  • Conference paper
Applications of Evolutionary Computing (EvoWorkshops 2006)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3907))

Included in the following conference series:

Abstract

In this paper, we present an efficient method for detecting collisions between highly deformable objects, which is a combination of newly developed stochastic method and Particle Swarm Optimization (PSO) algorithm. Firstly, our algorithm samples primitive pairs within the models to construct a discrete binary search space for PSO, and in this way user can balance performance and detection quality. Besides a particle update process is added in every time step to handle the dynamic environments caused by deformations. Our algorithm is also very general that makes no assumptions about the input models and doesn’t need to store additional data structures either. In the end, we give the precision and efficiency evaluation about the algorithm and find it might be a reasonable choice for complex deformable models in collision detection systems.

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 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
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. Teschner, M., Kimmerle, S., Heidelberger, B.: Collision detection for deformable objects. Eurographics, State of the Art Report (2005)

    Google Scholar 

  2. Uno, S., Slater, M.: The sensitivity of presence to collision response. In: Proc. of IEEE Virtual Reality Annual International Symposium (VRAIS) (1997)

    Google Scholar 

  3. Kennedy, J., Eberhart, R.: Particle Swarm Optimization. In: IEEE International Conference on Neural Networks, Perth, Australia (1995)

    Google Scholar 

  4. Shi, Y.H., Eberhart, R.C.: Parameter Selection in Particle Swarm Optimization. In: The 7th Annual Conference on Evolutionary Programming, San Diego, USA (1998)

    Google Scholar 

  5. Carlisle, A., Dozier, G.: Adapting Particle Swarm Optimization to Dynamic Environments. In: Proceedings of International Conference on Artificial Intelligence, Las Vegas, Nevada, USA, pp. 429–434 (2000)

    Google Scholar 

  6. Eberhart, R., Shi, Y.: Comparison between Genetic Algorithms and Particle Swarm Optimization. In: The 7th Annual Conference on Evolutionary Programming, San Diego, USA (1998)

    Google Scholar 

  7. Smith, A., Kitamura, Y., Takemura, H., Kishino, F.: A Simple and Efficient Method for Accurate Collision Detection Among Deformable Polyhedral Objects in Arbitrary Motion. In: Proceedings of the IEEE Virtual Reality Annual International Symposium, pp. 136–145 (1995)

    Google Scholar 

  8. Ganovelli, F., Dingliana, J., O’Sullivan, C.: BucketTree: Improving Collision Detection between Deformable Objects. In: Spring Conference in Computer Graphic, Bratislava, pp. 156–163 (2000)

    Google Scholar 

  9. Van den Bergen, G.: Efficient Collision Detection of Complex Deformable Models using AABB Trees. Journal of Graphics Tools 2(4), 1–14 (1997)

    MATH  Google Scholar 

  10. Van det Bergen, G.: SOLID. Software Library for Interference Detection 2 (1999), Available at http://www.win.tue.nl/cs/tt/gino/solid

  11. Klein, J., Zachmann, G.: Adb-trees: Controlling the error of time-critical collision detection. In: Proceedings of Vision, Modeling and Visualization (2003)

    Google Scholar 

  12. Kimmerle, S., Nesme, M., Faure, F.: Hierarchy accelerated stochastic collision detection. In: Proceedings of Vision, Modeling, Visualization, pp. 307–314 (2004)

    Google Scholar 

  13. Larsson, T., Akenine-móller, T.: Collision detection for continuously deforming bodies. In: Eurographics (2001)

    Google Scholar 

  14. Eberhart, R., Shi, Y.: Tracking and optimizing dynamic systems with particle swarm. In: Proc. Congress on Evolutionary Computation, Piscataway, pp. 94–97. IEEE Press, NJ (2001)

    Google Scholar 

  15. Hu, X., Eberhart, R.C.: Adaptive particle swarm optimization: detection and response to dynamic systems. In: Proceedings of the IEEE Congress on Evolutionary Computation, CEC, pp. 1666–1670. IEEE Press, Los Alamitos (2002)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Key Laboratory of Symbol, Computation and Knowledge Engineering of the Ministry of Education, College of Computer Science and Technology, Jilin University, Changchun, 130012, P.R. China

    Wang Tianzhu, Li Wenhui, Wang Yi, Ge Zihou & Han Dongfeng

Authors
  1. Wang Tianzhu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Li Wenhui
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Wang Yi
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Ge Zihou
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Han Dongfeng
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Johannes Gutenberg University, Mainz, Germany

    Franz Rothlauf

  2. Institute AIFB, University of Karlsruhe, 76128, Karlsruhe, Germany

    Jürgen Branke

  3. Dipartimento di Ingegneria dell’Informazione, Università di Parma,  

    Stefano Cagnoni

  4. Centre of Informatics and Systems of the University of Coimbra,  

    Ernesto Costa

  5. Dept. LCC, Universidad de Málaga, Spain

    Carlos Cotta

  6. Institute of Computer Science, University of Bremen, 28359, Bremen, Germany

    Rolf Drechsler

  7. INRIA Saclay - Ile-de-France, Parc Orsay Université, 4, rue Jacques Monod, 91893, ORSAY Cedex, France

    Evelyne Lutton

  8. CISUC, Department of Informatics Engineering, University of Coimbra, Polo II of the University of Coimbra, 3030, Coimbra, Portugal

    Penousal Machado

  9. Dartmouth College, Lebanon, NH, USA

    Jason H. Moore

  10. Universidade de A Coruña, CP 15071, A Coruña, Spain

    Juan Romero

  11. School of Computing Sciences, UEA Norwich, University of East Anglia, NR4 7TJ, Norwich, UK

    George D. Smith

  12. Dipartimento di Automatica e Informatica, Politecnico di Torino, Italy

    Giovanni Squillero

  13. Kyushu University, Japan

    Hideyuki Takagi

Rights and permissions

Reprints and permissions

Copyright information

© 2006 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Tianzhu, W., Wenhui, L., Yi, W., Zihou, G., Dongfeng, H. (2006). An Adaptive Stochastic Collision Detection Between Deformable Objects Using Particle Swarm Optimization. In: Rothlauf, F., et al. Applications of Evolutionary Computing. EvoWorkshops 2006. Lecture Notes in Computer Science, vol 3907. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11732242_40

Download citation

  • DOI: https://doi.org/10.1007/11732242_40

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-33237-4

  • Online ISBN: 978-3-540-33238-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation