LineUp : computing chain-based physical transformation

In this article, we introduce a novel method that can generate a sequence of physical transformations between 3D models with different shape and topology. Feasible transformations are realized on a chain structure with connected components that are 3D printed. Collision-free motions are computed to...

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Main Authors: Yu, Minjing, Ye, Zipeng, Liu, Yong-Jin, He, Ying, Wang, Charlie Chang Ling
Other Authors: School of Computer Science and Engineering
Format: Article
Language:English
Published: 2020
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Online Access:https://hdl.handle.net/10356/144752
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1447522020-11-23T06:45:17Z LineUp : computing chain-based physical transformation Yu, Minjing Ye, Zipeng Liu, Yong-Jin He, Ying Wang, Charlie Chang Ling School of Computer Science and Engineering Engineering::Computer science and engineering Computing Methodologies Computing Graphics In this article, we introduce a novel method that can generate a sequence of physical transformations between 3D models with different shape and topology. Feasible transformations are realized on a chain structure with connected components that are 3D printed. Collision-free motions are computed to transform between different configurations of the 3D printed chain structure. To realize the transformation between different 3D models, we first voxelize these input models into a similar number of voxels. The challenging part of our approach is to generate a simple path—as a chain configuration to connect most voxels. A layer-based algorithm is developed with theoretical guarantee of the existence and the path length. We find that collision-free motion sequence can always be generated when using a straight line as the intermediate configuration of transformation. The effectiveness of our method is demonstrated by both the simulation and the experimental tests taken on 3D printed chains. This work is supported by the National Science Foundation of China (61725204, 61432003, 61521002 and 61661130156) and the Royal Society-Newton Advanced Fellowship (NA150431). 2020-11-23T06:45:17Z 2020-11-23T06:45:17Z 2019 Journal Article Yu, M., Ye, Z., Liu, Y.-J., He, Y., & Wang, C. C. L. (2019). LineUp : computing chain-based physical transformation. ACM Transactions on Graphics, 38(1), 11-. doi:10.1145/3269979 0730-0301 https://hdl.handle.net/10356/144752 10.1145/3269979 1 38 en ACM Transactions on Graphics © 2019 Association for Computing Machinery. 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
Computing Methodologies
Computing Graphics
spellingShingle Engineering::Computer science and engineering
Computing Methodologies
Computing Graphics
Yu, Minjing
Ye, Zipeng
Liu, Yong-Jin
He, Ying
Wang, Charlie Chang Ling
LineUp : computing chain-based physical transformation
description In this article, we introduce a novel method that can generate a sequence of physical transformations between 3D models with different shape and topology. Feasible transformations are realized on a chain structure with connected components that are 3D printed. Collision-free motions are computed to transform between different configurations of the 3D printed chain structure. To realize the transformation between different 3D models, we first voxelize these input models into a similar number of voxels. The challenging part of our approach is to generate a simple path—as a chain configuration to connect most voxels. A layer-based algorithm is developed with theoretical guarantee of the existence and the path length. We find that collision-free motion sequence can always be generated when using a straight line as the intermediate configuration of transformation. The effectiveness of our method is demonstrated by both the simulation and the experimental tests taken on 3D printed chains.
author2 School of Computer Science and Engineering
author_facet School of Computer Science and Engineering
Yu, Minjing
Ye, Zipeng
Liu, Yong-Jin
He, Ying
Wang, Charlie Chang Ling
format Article
author Yu, Minjing
Ye, Zipeng
Liu, Yong-Jin
He, Ying
Wang, Charlie Chang Ling
author_sort Yu, Minjing
title LineUp : computing chain-based physical transformation
title_short LineUp : computing chain-based physical transformation
title_full LineUp : computing chain-based physical transformation
title_fullStr LineUp : computing chain-based physical transformation
title_full_unstemmed LineUp : computing chain-based physical transformation
title_sort lineup : computing chain-based physical transformation
publishDate 2020
url https://hdl.handle.net/10356/144752
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