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http://hdl.handle.net/10119/15478
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Title: | Origami Folding Sequence Generation Using Discrete Particle Swarm Optimization |
Authors: | Bui, Ha-Duong Jeong, Sungmoon Chong, Nak Young Mason, Matthew |
Keywords: | mathematical origami folding sequence combinatorial optimization particle swarm optimization |
Issue Date: | 2017-10-24 |
Publisher: | Springer |
Magazine name: | Lecture Notes in Computer Science |
Volume: | 10637 |
Start page: | 484 |
End page: | 493 |
DOI: | 10.1007/978-3-319-70093-9_51 |
Abstract: | This paper proposes a novel approach to automating origamior paper folding. The folding problem is formulated as a combinatorial optimization problem to automatically find feasible folding sequences toward the desired shape from a generic crease pattern, minimizing the dissimilarity between the current and desired origami shapes. Specifically, we present a discrete particle swarm optimization algorithm, which can take advantage of the classical particle swarm optimization algorithm in a discrete folding action space. Through extensive numerical experiments, we have shown that the proposed approach can generate an optimum origami folding sequence by iteratively minimizing the Hausdorff distance, a dissimilarity metric between two geometric shapes. Moreover, an in-house origami simulator is newly developed to visualize the sequence of origami folding. |
Rights: | This is the author-created version of Springer, Ha-Duong Bui, Sungmoon Jeong, Nak Young Chong, Matthew Mason, Lecture Notes in Computer Science, 10637, 2017, 484-493. The original publication is available at www.springerlink.com, http://dx.doi.org/10.1007/978-3-319-70093-9_51 |
URI: | http://hdl.handle.net/10119/15478 |
Material Type: | author |
Appears in Collections: | b10-1. 雑誌掲載論文 (Journal Articles)
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