Autonomous Virtual Agent Navigation in Virtual Environments
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 vir...
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World Academy of Science, Engineering and Technology (WASET)
2010
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my.utp.eprints.28502014-03-21T21:34:27Z Autonomous Virtual Agent Navigation in Virtual Environments Jaafar, J. McKenzie, E. QA76 Computer software 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 identifies which part of an obstacle can be seen from the position of the virtual agent. This information is require for virtual agent to coordinate navigation in virtual environment. The virtual 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. World Academy of Science, Engineering and Technology (WASET) 2010-08-29 Article PeerReviewed http://www.waset.org/journals/ijcie/ Jaafar, J. and McKenzie, E. (2010) Autonomous Virtual Agent Navigation in Virtual Environments. International Journal of Computer and Information Engineering, 4 (1). pp. 19-26. http://eprints.utp.edu.my/2850/ |
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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 identifies which part of an obstacle can be seen from the position of the virtual agent. This information is require for virtual agent to coordinate navigation in virtual environment. The virtual 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. |
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Article |
author |
Jaafar, J. McKenzie, E. |
author_facet |
Jaafar, J. McKenzie, E. |
author_sort |
Jaafar, J. |
title |
Autonomous Virtual Agent Navigation in Virtual Environments |
title_short |
Autonomous Virtual Agent Navigation in Virtual Environments |
title_full |
Autonomous Virtual Agent Navigation in Virtual Environments |
title_fullStr |
Autonomous Virtual Agent Navigation in Virtual Environments |
title_full_unstemmed |
Autonomous Virtual Agent Navigation in Virtual Environments |
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autonomous virtual agent navigation in virtual environments |
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World Academy of Science, Engineering and Technology (WASET) |
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2010 |
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http://www.waset.org/journals/ijcie/ http://eprints.utp.edu.my/2850/ |
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1738655226464829440 |