Flocking for multi agent system : split and merge algorithm

The final year project is the extension of existing project with code name FAME. FAME is C# language game engine software application based on the open source rendering engine Orge3D developed to study and simulate steering behaviors of multi autonomous agents. Before this FYP, several s...

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Bibliographic Details
Main Author: Do, Bach Viet
Other Authors: Ong Yew Soon
Format: Final Year Project
Language:English
Published: 2010
Subjects:
Online Access:http://hdl.handle.net/10356/36267
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Institution: Nanyang Technological University
Language: English
Description
Summary:The final year project is the extension of existing project with code name FAME. FAME is C# language game engine software application based on the open source rendering engine Orge3D developed to study and simulate steering behaviors of multi autonomous agents. Before this FYP, several steering behaviors has been studied and implemented including arrival, goal seeking, wandering and flocking, the most interesting behavior. Flocking algorithm attempts to simulate the beautiful natural phenomenon of flocks of thousand birds, schools of countless fish or great herds of animals (In computer science, ―this gathering of mass individuals‖ are commonly termed flocking).Nonetheless, the problem of obstacle avoidance for flock of agents has not been studied before. In this project, the problem of a flock obstacle avoidance is analyzed. Inspired by the nature of flocking avoidance behavior, the obstacle avoidance should comprise of ways to split the whole flock to steer around the obstacle and merge back into the old flock afterward. This report is going to explain in the details algorithm developed during 8 months and show that it is able to produce realistic animation and deliver strong performance. In addition, in FAME, a steering agent is a combination of several steering behaviors, i.e, arrival behavior, goal seeking behavior, wandering behavior and flocking behavior. Adding one more obstacle avoidance behavior increases chances to cause conflicts and the optimization of steering behaviors has also not been thoroughly investigated before. Thus, the problem of steering behaviors optimization and solution are also discussed in this report.