ThingWorld: A multibody simulation system with low computational complexity

  • Alex P. Pentland
Visualization Techniques
Part of the Lecture Notes in Computer Science book series (LNCS, volume 492)


The ability to simulate complex physical situations in near-real-time is a critical element of many engineering and robotics applications. Unfortunately the computation cost of standard physical simulation methods increases rapidly as the situation becomes more complex. The result is that even when using the fastest supercomputers we are still able to interactively simulate only small, toy worlds. To solve this problem I have proposed changing the way we represent and simulate physics in order to reduce the computational complexity of physical simulation, thus making possible interactive simulation of complex situations. A prototype system, called ThingWorld, that makes use of these new representations has been implemented for UNIX computer systems and has demonstrated O(n) computational complexity (linear scaling of computational cost with increasing model complexity) for multibody dynamic simulations.


Nodal Point Constraint Satisfaction Collision Detection Storage Location Physical Simulation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. [1]
    Sutherland, I., (1963), Sketchpad: A Man-Machine Graphical Communications System, in Interactive Computer Graphics, in 1963 Spring Joint Computer Conference, reprinted in H. Freeman, ed., IEEE Comp. Soc., 1980, pp. 1–19.Google Scholar
  2. [2]
    Borning, A., (1979), Thinglab — a constraint-oriented simulation laboratory. SSL-79-3, Xerox PARC, Palo Alto, CA.Google Scholar
  3. [3]
    Tennenbaum, J., Pan, J., Glicksman, J., Hitson, B., Cutkosky, M., and Brown, D., (1989) Toward a Computer-Integrated Enterprise, Proceedings of the MIT-JSME Workshop on Cooperative Product Development, November 20–21, Cambridge, MAGoogle Scholar
  4. [4]
    Tomiyama, T., Kiriyama, T., and Yosshikawa, H., (1989) A Model Integration Mechanism for Concurrent Design, Proceedings of the MIT-JSME Workshop on Cooperative Product Development, November 20–21, Cambridge, MA.Google Scholar
  5. [5]
    Pentland, A., and Williams, J., (1989) Virtual Manufacturing, NSF Engineering Design Research Conference, pp. 301–316, June 11–14, Amherst, MA.Google Scholar
  6. [6]
    Gosling, J. (1983) Algebraic Constraints, CMU-CS-83-132, Ph. D. Thesis, Computer Science Dept., Carnegie-Mellon University, Pittsburgh, PA.Google Scholar
  7. [7]
    Steele, G., and Sussman, G. (1978) Constraints, Technical Report, M.I.T. AI Memo 502.Google Scholar
  8. [8]
    Witkin, A., Fleischer, K, and Barr, A., (1987) Energy Constraints on Parameterized Models, Proceedings of SIGGRAPH '87, Computing Graphics, Vol. 21, No. 4, pp 225–231.Google Scholar
  9. [9]
    Barzel, R., and Barr, A., (1988) A Modeling System Based on Dynamic Constraints, Proceedings of SIGGRAPH '87, Computer Graphics, Vol. 22, No. 4, pp 179–188.Google Scholar
  10. [10]
    Pentland, A., and Williams, J., (1989) Good Vibrations: Modal Analysis for Graphics and Animation, ACM Computer Graphics, (Siggraph 89) Vol. 23, No. 4, pp. 215–223Google Scholar
  11. [11]
    Anderson, J. S., and Bratos-Anderson, M., (1987) Solving Problems in Vibrations, Longman Scientific and Technical Publ., Essex, England.Google Scholar
  12. [12]
    Hahn, J., (1988) Realistic Animation of Rigid Bodies, Proceedings of SIGGRAPH '88, Computer Graphics, Vol. 22, No. 4, pp. 299–308.Google Scholar
  13. [13]
    Pentland, A. (1986) Perceptual Organization and the Representation of Natural Form, Artificial Intelligence Journal, Vol. 28, No. 2, pp. 1–38.Google Scholar
  14. [14]
    Blinn, J.F., and Newell, M.E., (1976) Texture and Reflection in Computer Generated Images, Comm. ACM, Vol. 19, No. 10, pp. 542–547.Google Scholar
  15. [15]
    Barr, A., (1984) Global and local deformations of solid primitives. Proceedings of SIGGRAPH '84, Computer Graphics 18, 3, 21–30Google Scholar
  16. [16]
    Gardiner, M. (1965) The superellipse: a curve that lies between the ellipse and the rectangle, Scientific American, September 1965.Google Scholar
  17. [17]
    Barr, A., (1981) Superquadrics and angle-preserving transformations, IEEE Computer Graphics and Application, 1 1–20Google Scholar
  18. [18]
    Pentland A., Essa I., Friedmann M., Horowitz B., Sclaroff S., and Starner T., The ThingWorld Modeling System, in Algorithms and Parallel VLSI Architectures, E.F. Deprettre (ed.), Elsevier Press, 1990.Google Scholar
  19. [19]
    Pentland, A., Automatic Extraction of Deformable Part Models, International Journal of Computer Vision, 107–126, 1990.Google Scholar
  20. [20]
    Blinn J., A Generalization of Algebraic Surface Drawing, ACM Transactions on Graphics, 1(3):235–256, July 1982.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1991

Authors and Affiliations

  • Alex P. Pentland
    • 1
  1. 1.Vision and Modeling Group, Room E15-387, The Media LabMassachusetts Institute of TechnologyCambridge

Personalised recommendations