Seminar • Computer Graphics — Computational Design of Complex Assemblies

Monday, March 25, 2019 10:30 am - 10:30 am EDT (GMT -04:00)

Peng Song, Research scientist
École polytechnique fédérale de Lausanne

3D assemblies refer to objects that combine multiple component parts into a structure/mechanism with a specific form and functionality. Due to the ability to make complex and large objects from simple and small parts, 3D assemblies are widely used, e.g., in toys, furniture, architecture, mechanical engineering, and robotics. Designing complex assemblies is a challenging problem since we need to consider not only the geometry of parts and their local joining, but also the aesthetic, structural, and functional performance of the whole assembly.

In this talk, I will outline a general computational approach for the fabrication-aware design of complex assemblies. The key ingredients of this approach include high-level assembly representations, geometric abstractions of physical properties, and advanced design exploration methods. I will focus on three examples of this approach: 1) interlocking assemblies with high structural stability; 2) reconfigurable assemblies that have multiple forms for use in different situations; and 3) functional mechanical assemblies that can display user-specified motions. All these designed assemblies are ready for fabrication, and their structural and functional performance have been validated in the physical experiments.


Bio: Peng Song is a research scientist at EPFL, working with Prof. Mark Pauly since October 2017. He received his B.S. degree from Harbin Institute of Technology in 2007, M.S. degree from Harbin Institute of Technology (Shenzhen) in 2009, and Ph.D. from Nanyang Technological University, Singapore in 2013.

His research interests lie in computer graphics, with a particular focus on the modelling, processing, design and fabrication of digital 3D geometry. His research works have been published in several leading journals and conferences, including ACM TOG, IEEE TVCG, CGF, and ACM CHI. 

More details about his research are available at https://songpenghit.github.io.