Optimal path planning algorithms in virtual environments

Path planning algorithm is a common algorithm applied in many fields of research specifically in robotic, games and Virtual Environments (VEs). Meanwhile, VE is a cutting edge technology that can add realistic visualization of a real world. Interaction within a VE requires animated characters to par...

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Bibliographic Details
Main Author: Hassan, Rohayanti
Format: Thesis
Language:English
Published: 2006
Subjects:
Online Access:http://eprints.utm.my/id/eprint/5500/1/RohayantiHassanMFSKSM2006.pdf
http://eprints.utm.my/id/eprint/5500/
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Summary:Path planning algorithm is a common algorithm applied in many fields of research specifically in robotic, games and Virtual Environments (VEs). Meanwhile, VE is a cutting edge technology that can add realistic visualization of a real world. Interaction within a VE requires animated characters to participate in such a way that they are able to navigate as well as plan the tour. Normally, in a large virtual exhibition area, a visitor tours to multiple sites before reaching the final destination. This may lead to several problems such as collision with obstacles, time-consuming journey, inefficient searching process and high utilization of computer memory. The main aim of the research was to find an efficient route tour approach that combines path finding, path planning and path optimization algorithm. In relation to that, A* algorithm was used as a path finding technique to plan a collision-free-path journey from one location to another. A* algorithm was also incorporated with Cell Mapping technique to speed up the searching process. In addition, Extended Prim algorithm was applied to shorten the travelling time and a virtual exhibition area was used as a domain to execute and analyse the algorithms performances. The results show that the Extended Prim algorithm has succeeded in reducing the travelling time up to 60 percent. Furthermore, the results also revealed that the searching process and computer memory utilization significantly improved up to 22 percent and 55 percent, respectively. It was also found that the combination of A* algorithm and Cell Mapping technique can be applied to a wide range of VE’s sizes.