Dense, Interlocking-Free and Scalable Spectral Packing of Generic 3D Objects
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3592126.pdf
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61.42 MB
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Author(s)
Cui, Qiaodong
Rong, Victor
Chen, Desai
Matusik, Wojciech
Date Issued
August 1, 2023
Journal
ACM Transactions on Graphics
Publisher
ACM
Citation
Cui, Qiaodong, Rong, Victor, Chen, Desai and Matusik, Wojciech. 2023. "Dense, Interlocking-Free and Scalable Spectral Packing of Generic 3D Objects." ACM Transactions on Graphics, 42 (4).
Version
Final published version
Abstract
Packing 3D objects into a known container is a very common task in many industries such as packaging, transportation, and manufacturing. This important problem is known to be NP-hard and even approximate solutions are challenging. This is due to the difficulty of handling interactions between objects with arbitrary 3D geometries and a vast combinatorial search space. Moreover, the packing must be {\it interlocking-free} for real-world applications. In this work, we first introduce a novel packing algorithm to search for placement locations given an object. Our method leverages a discrete voxel representation. We formulate collisions between objects as correlations of functions computed efficiently using Fast Fourier Transform (FFT). To determine the best placements, we utilize a novel cost function, which is also computed efficiently using FFT. Finally, we show how interlocking detection and correction can be addressed in the same framework resulting in interlocking-free packing. We propose a challenging benchmark with thousands of 3D objects to evaluate our algorithm. Our method demonstrates state-of-the-art performance on the benchmark when compared to existing methods in both density and speed.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Terms of Use
Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
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DOI of Published Version
https://doi.org/10.1145/3592126
