Hierarchical planning-based crowd formation

Team formation with realistic crowd simulation behavior is a challenge in computer graphics, multiagent control, and social simulation. In this study, we propose a framework of crowd formation via hierarchical planning, which includes cooperative-task, coordinated-behavior, and action-control planni...

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Main Authors: Liu, Na, Wang, Xingce, Liu, Shaolong, Wu, Zhongke, He, Jiale, Cheng, Peng, Miao, Chunyan, Thalmann, Nadia Magnenat
Other Authors: School of Computer Science and Engineering
Format: Article
Language:English
Published: 2021
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Online Access:https://hdl.handle.net/10356/150754
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1507542021-08-02T02:17:55Z Hierarchical planning-based crowd formation Liu, Na Wang, Xingce Liu, Shaolong Wu, Zhongke He, Jiale Cheng, Peng Miao, Chunyan Thalmann, Nadia Magnenat School of Computer Science and Engineering Engineering::Computer science and engineering Fuzzy Logic Control Gaze-movement Angle Team formation with realistic crowd simulation behavior is a challenge in computer graphics, multiagent control, and social simulation. In this study, we propose a framework of crowd formation via hierarchical planning, which includes cooperative-task, coordinated-behavior, and action-control planning. In cooperative-task planning, we improve the grid potential field to achieve global path planning for a team. In coordinated-behavior planning, we propose a time–space table to arrange behavior scheduling for a movement. In action-control planning, we combine the gaze-movement angle model and fuzzy logic control to achieve agent action. Our method has several advantages. (1) The hierarchical architecture is guaranteed to match the human decision process from high to low intelligence. (2) The agent plans his behavior only with the local information of his neighbor; the global intelligence of the group emerges from these local interactions. (3) The time–space table fully utilizes three-dimensional information. Our method is verified using crowds of various densities, from sparse to dense, employing quantitative performance measures. The approach is independent of the simulation model and can be extended to other crowd simulation tasks. The authors sincerely thank the referees and anonymous reviewers for their helpful comments and suggestions. This research was supported by the National Key Research and Development Program of China (2017YFB1002604, 2017YFB100-2600, and 2017YFB1402100), the National Key Cooperation between the BRICS of China (2017YFE0100500), and the Beijing Municipal Natural Science Foundation of China (4172033). 2021-08-02T02:17:55Z 2021-08-02T02:17:55Z 2019 Journal Article Liu, N., Wang, X., Liu, S., Wu, Z., He, J., Cheng, P., Miao, C. & Thalmann, N. M. (2019). Hierarchical planning-based crowd formation. Computer Animation and Virtual Worlds, 30(6), e1875-. https://dx.doi.org/10.1002/cav.1875 1546-4261 0000-0002-4572-4155 https://hdl.handle.net/10356/150754 10.1002/cav.1875 2-s2.0-85065093945 6 30 e1875 en Computer Animation and Virtual Worlds © 2019 John Wiley & Sons, Ltd. All rights reserved.
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Computer science and engineering
Fuzzy Logic Control
Gaze-movement Angle
spellingShingle Engineering::Computer science and engineering
Fuzzy Logic Control
Gaze-movement Angle
Liu, Na
Wang, Xingce
Liu, Shaolong
Wu, Zhongke
He, Jiale
Cheng, Peng
Miao, Chunyan
Thalmann, Nadia Magnenat
Hierarchical planning-based crowd formation
description Team formation with realistic crowd simulation behavior is a challenge in computer graphics, multiagent control, and social simulation. In this study, we propose a framework of crowd formation via hierarchical planning, which includes cooperative-task, coordinated-behavior, and action-control planning. In cooperative-task planning, we improve the grid potential field to achieve global path planning for a team. In coordinated-behavior planning, we propose a time–space table to arrange behavior scheduling for a movement. In action-control planning, we combine the gaze-movement angle model and fuzzy logic control to achieve agent action. Our method has several advantages. (1) The hierarchical architecture is guaranteed to match the human decision process from high to low intelligence. (2) The agent plans his behavior only with the local information of his neighbor; the global intelligence of the group emerges from these local interactions. (3) The time–space table fully utilizes three-dimensional information. Our method is verified using crowds of various densities, from sparse to dense, employing quantitative performance measures. The approach is independent of the simulation model and can be extended to other crowd simulation tasks.
author2 School of Computer Science and Engineering
author_facet School of Computer Science and Engineering
Liu, Na
Wang, Xingce
Liu, Shaolong
Wu, Zhongke
He, Jiale
Cheng, Peng
Miao, Chunyan
Thalmann, Nadia Magnenat
format Article
author Liu, Na
Wang, Xingce
Liu, Shaolong
Wu, Zhongke
He, Jiale
Cheng, Peng
Miao, Chunyan
Thalmann, Nadia Magnenat
author_sort Liu, Na
title Hierarchical planning-based crowd formation
title_short Hierarchical planning-based crowd formation
title_full Hierarchical planning-based crowd formation
title_fullStr Hierarchical planning-based crowd formation
title_full_unstemmed Hierarchical planning-based crowd formation
title_sort hierarchical planning-based crowd formation
publishDate 2021
url https://hdl.handle.net/10356/150754
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