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2010 Seventh International Conference on Information Technology
Path Planning for Virtual Human Motion Using Improved A* Star Algorithm
Las Vegas, Nevada, USA
April 12-April 14
ISBN: 978-0-7695-3984-3
ASCII Text
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Junfeng Yao, Chao Lin, Xiaobiao Xie, Andy JuAn Wang, Chih-Cheng Hung, "Path Planning for Virtual Human Motion Using Improved A* Star Algorithm," Information Technology: New Generations, Third International Conference on, pp. 1154-1158, 2010 Seventh International Conference on Information Technology, 2010.
 
 
BibTex
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@article{ 10.1109/ITNG.2010.53,
author = {Junfeng Yao and Chao Lin and Xiaobiao Xie and Andy JuAn Wang and Chih-Cheng Hung},
title = {Path Planning for Virtual Human Motion Using Improved A* Star Algorithm},
journal ={Information Technology: New Generations, Third International Conference on},
volume = {0},
year = {2010},
isbn = {978-0-7695-3984-3},
pages = {1154-1158},
doi = {http://doi.ieeecomputersociety.org/10.1109/ITNG.2010.53},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
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TY - CONF
JO - Information Technology: New Generations, Third International Conference on
TI - Path Planning for Virtual Human Motion Using Improved A* Star Algorithm
SN - 978-0-7695-3984-3
SP1154
EP1158
A1 - Junfeng Yao,
A1 - Chao Lin,
A1 - Xiaobiao Xie,
A1 - Andy JuAn Wang,
A1 - Chih-Cheng Hung,
PY - 2010
KW - Improved A* Algorithm
KW - Evaluation Function
KW - Path Optimization
KW - Manual Searching Marker
VL - 0
JA - Information Technology: New Generations, Third International Conference on
ER -
 
Calculating and generating optimal motion path automatically is one of the key issues in virtual human motion path planning. To solve the point, the improved A* algorithm has been analyzed and realized in this paper, we modified the traditional A* algorithm by weighted processing of evaluation function, which made the searching steps reduced from 200 to 80 and searching time reduced from 4.359s to 2.823s in the feasible path planning. The artificial searching marker, which can escape from the barrier trap effectively and quickly, is also introduced to avoid searching the invalid region repeatedly, making the algorithm more effective and accurate in finding the feasible path in unknown environments. We solve the issue of virtual human's obstacle avoidance and navigation through optimizing the feasible path to get the shortest path.
Index Terms:
Improved A* Algorithm, Evaluation Function, Path Optimization, Manual Searching Marker
Citation:
Junfeng Yao, Chao Lin, Xiaobiao Xie, Andy JuAn Wang, Chih-Cheng Hung, "Path Planning for Virtual Human Motion Using Improved A* Star Algorithm," itng, pp.1154-1158, 2010 Seventh International Conference on Information Technology, 2010
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