Physics-based Modeling of Printable Shapes

As the 3D printing technology starts to revolutionize how things are made in everyday life, it still suffers from many limitations, such as long printing time, expensive printing materials, and limited printing volume. To address these limitations, my research team investigates physics-based modeling of printable shapes, by leveraging our expertise in physics-based simulation.

A level-set-based partitioning framework          A natural way to reduce the printing time and overcome the printing volume limit is to partition a large 3D model into pieces, each of which can be quickly built in parallel by small printers. The main question is how to define and optimize the partitioning, so that it can meet various quality criteria. Inspired by the wide use of level set methods in image and mesh segmentation, we proposed a level-set-based framework for the partitioning of printable shapes. Under this framework, we presented a series of level set methods to improve the intrinsic qualities of the partitioning, such as boundary smoothness, gap invisibility, and strength against separation. Meanwhile, we developed a physics-based packing algorithm, which can work as a metric for level set methods to reduce the space occupied by the pieces within a printer or container. This framework has already demonstrated its effectiveness and flexibility in the design of high-quality partitioning models, which cannot be easily produced by previous methods.

Future research          Under the proposed level-set-based framework, I plan to further investigate better algorithms to address multiple printability issues. I am also interested in level set methods for optimizing support structures of partitioned pieces within a printer or container. Finally, I would like to improve the strength of an assembled model by struts and/or connectors, based on our ongoing research on real-time physics-based simulation.


Miaojun Yao, Zhili Chen, Linjie Luo, Rui Wang and Huamin Wang. 2015. Level-set-based partitioning and packing optimization of a printable model. ACM Transactions on Graphics (SIGGRAPH Asia), vol. 34, no. 6.
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