DocumentCode :
2288095
Title :
A Museum Visitors Guide with the A* pathfinding algorithm
Author :
Uang, Zhig ; Van Doren, Michael
Author_Institution :
Dept. of Math & Comput. Sci., Valdosta State Univ., Valdosta, GA, USA
Volume :
1
fYear :
2011
fDate :
10-12 June 2011
Firstpage :
62
Lastpage :
66
Abstract :
The A* algorithm is proven to be one of the most, if not the most, used AI pathfinding algorithm in game development today. Current development effort is now focused on optimizing the A* algorithm and applying it to solve real-world problems. In this paper, we present a Museum Visitors Guide (MVG) application with the A* pathfinding algorithm that helps museum visitors to make the most of their visit. The A* algorithm is optimized in a number of ways. First, the shortest path between the visitor´s current location and the goal art piece is dynamically produced in response to the changes of the exhibition floor plans. Secondly, visitors are allowed to select multiple works of art that they want to see. The best path that our MVG finds out covers them all. Thirdly, multiple optimum and load-balanced paths are discovered when there are multiple targets - a feature that is very useful for emergencies, e.g., for firefighters to put out the flames. To demonstrate that our MVG is well functional, flexible, and even ready to migrate to hand-held mobile platforms, we will show the running results of our simulation in the end of this paper.
Keywords :
art; artificial intelligence; graph theory; mobile computing; museums; resource allocation; A* pathfinding algorithm; AI pathfinding algorithm; art piece; exhibition floor plans; game development; handheld mobile platform; load balanced path; multiple art works; museum visitors guide application; shortest path; A* Pathfinding Algorithm; Artificial Intelligence; Computer Simulation and Modeling; Optimization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Science and Automation Engineering (CSAE), 2011 IEEE International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-8727-1
Type :
conf
DOI :
10.1109/CSAE.2011.5953171
Filename :
5953171
Link To Document :
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