Efficient simulation of large-scale urban environment with adaptive multiple-scene management

Project sizes and complexities of 3D Games and Simulations have increased drastically during the last ten years. Nowadays, a large number of applications have increasing scene complexity with non-scene-boundaries and contain many types of objects, both outdoors and indoors. There is, however, no gen...

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Main Author: Le, Minh Duc
Other Authors: Seah, Hock Soon
Format: Theses and Dissertations
Language:English
Published: 2014
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Online Access:http://hdl.handle.net/10356/61564
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-615642023-03-04T00:38:14Z Efficient simulation of large-scale urban environment with adaptive multiple-scene management Le, Minh Duc Seah, Hock Soon School of Computer Engineering Game Lab DRNTU::Engineering::Computer science and engineering Project sizes and complexities of 3D Games and Simulations have increased drastically during the last ten years. Nowadays, a large number of applications have increasing scene complexity with non-scene-boundaries and contain many types of objects, both outdoors and indoors. There is, however, no general scene management system that can efficiently handle all scene types. It is already a heavy burden to deal with each scene individually. It definitely becomes very challenging to handle the combination of multiple-scene types. Another challenge is the increasing complexity of Physics and Artificial Intelligence (AI) simulation. Optimization becomes harder especially when there are a lot of agents involved and when resources are limited. There are also too many high-level algorithmic choices that require years of experience to master and identify the most suitable algorithms for specific tasks. We identify these challenges as our main research thrusts. Our approach is to research on high-quality scene management techniques to enhance real-time rendering performances of graphics pipeline and better support for handling AI and dynamic objects. As a core design concept, we decouple the scene graph structure from its content and flattening the inheritance structure of the scene graph and its data nodes. This provides an elegant and powerful architecture that allows for greater accommodation for various scene types as well as easy implementation of alternate data types. As the main research contributions, we proposed an Adaptive Multiple-Scene Management Framework (AMS) that can seamlessly handle all scene types as individuals or as a combination. We also identified a logical linkage between scene management concept and the hierarchical structures within the methodologies to handle AI and dynamic objects. We conceptualized this linkage at a higher level: using our proposed multiple-scene management framework to optimize AI and Physics activities such as pathfinding, decision-making, formation, collision detection and handling large number of dynamic objects. Keywords: scene graph, scene management, level of detail, culling, AI, dynamic object Master of Engineering (SCE) 2014-06-11T08:19:57Z 2014-06-11T08:19:57Z 2014 2014 Thesis http://hdl.handle.net/10356/61564 en 105 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering::Computer science and engineering
spellingShingle DRNTU::Engineering::Computer science and engineering
Le, Minh Duc
Efficient simulation of large-scale urban environment with adaptive multiple-scene management
description Project sizes and complexities of 3D Games and Simulations have increased drastically during the last ten years. Nowadays, a large number of applications have increasing scene complexity with non-scene-boundaries and contain many types of objects, both outdoors and indoors. There is, however, no general scene management system that can efficiently handle all scene types. It is already a heavy burden to deal with each scene individually. It definitely becomes very challenging to handle the combination of multiple-scene types. Another challenge is the increasing complexity of Physics and Artificial Intelligence (AI) simulation. Optimization becomes harder especially when there are a lot of agents involved and when resources are limited. There are also too many high-level algorithmic choices that require years of experience to master and identify the most suitable algorithms for specific tasks. We identify these challenges as our main research thrusts. Our approach is to research on high-quality scene management techniques to enhance real-time rendering performances of graphics pipeline and better support for handling AI and dynamic objects. As a core design concept, we decouple the scene graph structure from its content and flattening the inheritance structure of the scene graph and its data nodes. This provides an elegant and powerful architecture that allows for greater accommodation for various scene types as well as easy implementation of alternate data types. As the main research contributions, we proposed an Adaptive Multiple-Scene Management Framework (AMS) that can seamlessly handle all scene types as individuals or as a combination. We also identified a logical linkage between scene management concept and the hierarchical structures within the methodologies to handle AI and dynamic objects. We conceptualized this linkage at a higher level: using our proposed multiple-scene management framework to optimize AI and Physics activities such as pathfinding, decision-making, formation, collision detection and handling large number of dynamic objects. Keywords: scene graph, scene management, level of detail, culling, AI, dynamic object
author2 Seah, Hock Soon
author_facet Seah, Hock Soon
Le, Minh Duc
format Theses and Dissertations
author Le, Minh Duc
author_sort Le, Minh Duc
title Efficient simulation of large-scale urban environment with adaptive multiple-scene management
title_short Efficient simulation of large-scale urban environment with adaptive multiple-scene management
title_full Efficient simulation of large-scale urban environment with adaptive multiple-scene management
title_fullStr Efficient simulation of large-scale urban environment with adaptive multiple-scene management
title_full_unstemmed Efficient simulation of large-scale urban environment with adaptive multiple-scene management
title_sort efficient simulation of large-scale urban environment with adaptive multiple-scene management
publishDate 2014
url http://hdl.handle.net/10356/61564
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