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The Visual Computer

, Volume 26, Issue 9, pp 1183–1199 | Cite as

Natural steering behaviors for virtual pedestrians

  • Renato SilveiraEmail author
  • Fábio Dapper
  • Edson Prestes
  • Luciana Nedel
Original Article

Abstract

The animation of humanoids in real-time applications is yet a challenge if the problem involves attaining a precise location in a virtual world (path-planning), moving realistically according to its own personality, intentions and mood (motion planning). In this paper we propose a formally complete and low-cost solution based upon boundary value problems (BVP) to control steering behaviors of characters in dynamic environments. We use a potential field formalism that allows synthetic actors to move negotiating space, avoiding collisions, and attaining goals, while producing very individual paths. The individuality of each character can be set by changing its inner field parameters leading to a broad range of possible behaviors without jeopardizing its performance. To illustrate the technique potentialities, some results exploring situations as steering behavior in corridors with collision avoidance and competition for a goal, and searching for objects in unknown environments are presented and discussed. A proposal to automatically change the size of the field of view of each agent, producing different behaviors is also a contribution of this paper. Some comments about performance are also made to help the reader to evaluate the potential of the method.

Humanoid simulation Path planning Steering behavior Harmonic functions Boundary value problems 

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References

  1. 1.
    Burgess, R.G., Darken, C.J.: Realistic human path-planning using fluid simulation. In: Proc. of Behavior Representation in Modeling and Simulation (BRIMS) (2004) Google Scholar
  2. 2.
    CAVIAR: EC funded caviar project/ist 2001 37540. http://homepages.inf.ed.ac.uk/rbf/caviar/. Last access: October 2009
  3. 3.
    Choi, M.G., Lee, J., Shin, S.Y.: Planning biped locomotion using motion capture data and probabilistic roadmaps. ACM Trans. Graph. 22(2), 182–203 (2003) CrossRefGoogle Scholar
  4. 4.
    Connolly, C.I., Grupen, R.A.: On the applications of harmonic functions to robotics. Int. J. Robot. Syst. 10, 931–946 (1993) zbMATHCrossRefGoogle Scholar
  5. 5.
    Dapper, F., Prestes, E., Nedel, L.P.: Generating steering behaviors for virtual humanoids using BVP control. Proc. Comput. Graph. Int. 1, 105–114 (2007) Google Scholar
  6. 6.
    James J. Kuffner, J.: Goal-directed navigation for animated characters using real-time path-planning and control. In: International Workshop on Modelling and Motion Capture Techniques for Virtual Environments, vol. 1537, pp. 171–186 (1998) Google Scholar
  7. 7.
    Kavraki, L., Svestka, P., Latombe, J.C., Overmars, M.: Probabilistic roadmaps for path-planning in high-dimensional configuration space. IEEE Trans. Robot. Autom. 12(4), 566–580 (1996) CrossRefGoogle Scholar
  8. 8.
    Khatib, O.: Commande dynamique dans l’espace opérational des robots manipulaters en présence d’obstacles. Ph.D. Thesis, École Nationale Supérieure de l’Aéronatique et de l’Espace, France (1980) Google Scholar
  9. 9.
    Koren, Y., Borenstein, J.: Potential field methods and their inherent limitations for mobile robot navigation. In: Proc. IEEE Int. Conf. Robotics and Automation, vol. 2, pp. 1398–1404 (1991) Google Scholar
  10. 10.
    LaValle, S.: Rapidly-exploring random trees: a new tool for path-planning. Technical Report 98-11, Computer Science Dept., Iowa State University (1998) Google Scholar
  11. 11.
    Mazarakis, G.P., Avaritsiotis, J.N.: A prototype sensor node for footstep detection. In: Proc. of the Second European Workshop on Wireless Sensor Networks, pp. 415–418. IEEE Press, New York (2005) CrossRefGoogle Scholar
  12. 12.
    Metoyer, R.A., Hodgins, J.K.: Reactive pedestrian path following from examples. Vis. Comput. 20(10), 635–649 (2004) CrossRefGoogle Scholar
  13. 13.
    Pelechano, N., O’brien, K., Silverman, B., Badler, N.: Crowd simulation incorporating agent psychological models, roles and communication. In: 1st Int’l Workshop on Crowd Simulation, pp. 21–30 (2005) Google Scholar
  14. 14.
    Pettre, J., Simeon, T., Laumond, J.: Planning human walk in virtual environments. In: IEEE/RSJ International Conference on Intelligent Robots and System, vol. 3, pp. 3048–3053 (2002) Google Scholar
  15. 15.
    Pettre, J., de Heras Ciechomski, P., Maim, J., Yersin, B., Laumond, J.P., Thalmann, D.: Real-time navigating crowds: scalable simulation and rendering: research articles. In: Computer Animation and Virtual Worlds, vol. 17, pp. 445–455 (2006) Google Scholar
  16. 16.
    Prestes, E., Engel, P.M., Trevisan, M., Idiart, M.A.: Exploration method using harmonic functions. Robot. Auton. Syst. 40(1), 25–42 (2002) CrossRefGoogle Scholar
  17. 17.
    Prestes, E., Trevisan, M., Idiart, M.A.P., Engel, P.M.: Bvp-exploration: further improvements. In: IEEE/RSJ International Conference on Intelligent Robots and Systems, vol. 3, pp. 3239–3244 (2003) Google Scholar
  18. 18.
    Reynolds, C.: Steering behaviors for autonomous characters. In: Game Developers Conference 1999, pp. 763–782 (1999) Google Scholar
  19. 19.
    Reynolds, C.: Big fast crowds on ps3. In: Proc. of the ACM SIGGRAPH Symposium on Videogames, pp. 113–121 (2006) Google Scholar
  20. 20.
    Shao, W., Terzopoulos, D.: Autonomous pedestrians. Graph. Models 69(5–6), 246–274 (2007) CrossRefGoogle Scholar
  21. 21.
    Tecchia, F., Loscos, C., Conroy, R., Chrysanthou, Y.: Agent behaviour simulator (abs): a platform for urban behaviour development. In: Proc. Game Technology (GTEC), pp. 17–21 (2001) Google Scholar
  22. 22.
    Treuille, A., Cooper, S., Popović, Z.: Continuum crowds. ACM Trans. Graph. 25, 1160–1168 (2006) CrossRefGoogle Scholar
  23. 23.
    Trevisan, M., Idiart, M.A., Prestes, E., Engel, P.M.: Exploratory navigation based on dynamic boundary value problems. J. Intell. Robot. Syst. 45, 101–114 (2006) CrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2009

Authors and Affiliations

  • Renato Silveira
    • 1
    Email author
  • Fábio Dapper
    • 1
  • Edson Prestes
    • 1
  • Luciana Nedel
    • 1
  1. 1.Institute of InformaticsFederal University of Rio Grande do SulPorto AlegreBrasil

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