Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 31100
Autonomous Virtual Agent Navigation in Virtual Environments

Authors: Jafreezal Jaafar, Eric McKenzie


This paper presents a solution for the behavioural animation of autonomous virtual agent navigation in virtual environments. We focus on using Dempster-Shafer-s Theory of Evidence in developing visual sensor for virtual agent. The role of the visual sensor is to capture the information about the virtual environment or identifie which part of an obstacle can be seen from the position of the virtual agent. This information is require for vitual agent to coordinate navigation in virtual environment. The virual agent uses fuzzy controller as a navigation system and Fuzzy α - level for the action selection method. The result clearly demonstrates the path produced is reasonably smooth even though there is some sharp turn and also still not diverted too far from the potential shortest path. This had indicated the benefit of our method, where more reliable and accurate paths produced during navigation task.

Keywords: Fuzzy Logic, Navigation, Agent, Demster Shafer

Digital Object Identifier (DOI):

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1265


[1] R. P. Darken and J. L. Sibert, "A toolset for navigation in virtual environments," in Proceedings of the 6th annual ACM symposium on User interface software and technology, (Atlanta, Georgia, United States), pp. 157-165, ACM Press, 1993.
[2] T. R. Wan, H. Chen, and R. Earnshaw, "Real-time path planning for navigation in unknown environment," in Theory and Practice of Computer Graphics 2003 (TPCG 03), (Birmingham, UK), p. 138, IEEE Computer Society, 2003.
[3] T. Y. Li, J. M. Lien, S. Y. Chiu, and T. H. Yu, "Automatically generating virtual guided tours," in -99 Computer Animation Conference, (Geneva, Switz), p. 99, IEEE, 1999.
[4] S. Bandi and D. Thalmann, "Path finding for human motion in virtual environments," Computational Geometry: Theory and Applications, vol. 15, no. 1-3, p. 103, 2000.
[5] P. Chaudhuri, R. Khandekar, D. Sethi, and P. Kalra, "An efficient central path algorithm for virtual navigation," in International Computer Graphics (CGI04), (Crete, Greece), p. 188, IEEE, 2004.
[6] M. Rook and A. Kamphuis, "Path finding using tactical information," in Eurographics/ACM SIGGRAPH Symposium on Computer Animation (2005) (K. Anjyo and P. Faloutsos, eds.), (Los Angeles, USA), pp. 18- 19, ACM SIGGRAPH, 2005.
[7] M. Stilman and J. J. Kuffner, "Navigation among movable obstacles: Real-time reasoning in complex environments," in 4th IEEE-RAS International Conference on Humanoid Robots, 2004, vol. 1, (Santa Monica, USA), p. 322, IEEE Inc., 2004.
[8] F. Lamarche and S. Donikian, "Crowd of virtual humans: a new approach for real time navigation in complex and structured environments," Computer Graphics Forum, vol. 23, no. 3, pp. 509-518, 2004.
[9] P. Tozour, "Search space representations," in AI Game Programming Wisdom 2 (S. Rabin, ed.), USA: Charles River Media Inc., 2003.
[10] Elusive, "Omicron bot," 1998.
[11] B. Salomon, M. Garber, C. L. Ming, and M. Dinesh, "Interactive navigation in complex environments using path planning," in 2003 Symposium on Interactive 3D graphics, (Monterey, California), pp. 41- 50, ACM Press, 2003.
[12] M. Lozano and J. Molina, "A neural approach to an attentive navigation for 3D intelligent virtual agents," in 2002 IEEE International Conference on Systems, Man and Cybernetics, vol. 6, (Hammamet, Tunisia), p. 5, IEEE, 2002.
[13] J. Velagic, B. Lacevic, and B. Perunicic, "A 3-level autonomous mobile robot navigation system designed by using reasoning/search approaches," Robotics and Autonomous Systems, vol. 54, no. 12, p. 989, 2006.
[14] H.-S. Seo, Y. So-Joeng, and O. Kyung-Whan, "Fuzzy reinforcement function for the intelligent agent to process vague goals," in Annual Conference of the North American Fuzzy Information Processing Society - NAFIPS, (Atlanta, GA, USA), p. 29, IEEE, Piscataway, NJ, USA, 2000.
[15] F. Wang, Study of an Adaptive and Multifunctional Computational Behaviour Generation Model for Virtual Creature. PhD thesis, University of Edinburgh, 2002.
[16] M. Piaggio, A. Sgorbissa, G. Vercelli, and R. Zaccaria, "Autonomous robot navigation using a reactive agent," in AI*IA 97: Advances in Artificial Intelligence, p. 96, 1997.
[17] J. J. Kuffner, Autonomous Agent for Real-Time Animation. PhD thesis, Stanford University, 1999.
[18] F. Wang and E. McKenzie, "A multi-agent based evolutionary artificial neural network for general navigation in unknown environments," in Third Annual Conference on Autonomous Agents, (Seattle, United States), pp. 154-159, ACM Press, 1999.
[19] G. Shafer, A Mathematical Theory of Evidence. Princeton, NJ: Princeton University Press, 1976.
[20] Y.-C. Kim, S.-B. Cho, and S.-R. Oh, "The dempster-shafer approach to map-building for an autonomous mobile robot with fuzzy controller," in 2002 AFSS International Conference on Fuzzy Systems, vol. 2275 of Lecture Notes in Artificial Intelligence - Advances in Soft Computing, (Calcutta, India), p. 40, Springer-Verlag, 2002.
[21] B. Kosko, Neural Networks and Fuzzy Systems: A Dynamical Systems Approach to Machine Intelligence. New Jersey: Prentice-Hall inc., 1992.
[22] J. Jaafar and E. McKenzie, "A reactive architecture for autonomous agent navigation using fuzzy logic," in Artificial Intelligence and Soft Computing 2007, (Palma de Mallorca, Spain), pp. 57-62, IASTED, 2007.
[23] J. Jaafar and E. McKenzie, "Behaviour coordination of virtual agent navigation using fuzzy logic," in International Conference on Fuzzy Systems (Fuzz-IEEE 2006), (Vancouver, Canada), pp. 1139-1145, IEEE, 2006.
[24] T. J. Ross, Fuzzy Logic with Engineering Application. West Sussex: John Wiley & Sons, 2 ed., 2004.
[25] L.-X. Wang, A Course on Fuzzy System and Control. London: Prentice- Hall International Inc., 1997.
[26] P. Pirjanian and H. I. Christensen, "Behavior coordination using multiple-objective decision making," in SPIE Conference on Intelligent Systems and Advanced Manufacturing, (Pittsburgh, USA), 1997.
[27] P. Maes, "How to do the right thing," Connection Science Journal, Special Issue on Hybrid Systems, pp. 291-323, 1989.
[28] C. Huang, A Study on The Fuzzy Ranking and Its Application on The Decision Support System. PhD thesis, Tamkang University, 1989.
[29] S. Mabuchi, "An approach to the comparison of fuzzy subsets with an alpha-cut dependent index," IEEE Transactions on Systems, Man and Cybernetics, vol. 18, no. 2, p. 264, 1988.
[30] Y. Yuan, "Criteria for evaluating fuzzy ranking methods," Fuzzy Sets and Systems, vol. 43, no. 2, pp. 139-157, 1991.
[31] F. Choobineh and H. Li, "An index for ordering fuzzy numbers," Fuzzy Sets and Systems, vol. 54, no. 3, p. 287, 1993.
[32] T. Y. Chen and Y. T. Yu, "On the criteria of allocating test cases under uncertainty," in Fourth Asia-Pacific Software Engineering and International Computer Science Conference (APSEC-97 / ICSC-97), (Hong Kong), p. 405, IEEE, 1997.
[33] Y. Cang and W. Danwei, "Novel behavior fusion method for the navigation of mobile robots," in 2000 IEEE International Conference on Systems, Man and Cybernetics, vol. 5 of Proceedings of the IEEE International Conference on Systems, Man and Cybernetics, (Nashville, USA), p. 3526, IEEE, 2000.