The Computational Fabrication Group at the MIT Computer Science and Artificial Intelligence Laboratory investigates problems in digital manufacturing and computer graphics. The group is led by Professor Wojciech Matusik.

News

08/08/2019
Computer-aided knitting covered by BBC!

During the past week, Alex's two recent papers on knitting Neural Inverse Knitting: From Images to Manufacturing Instructions (ICML 19) and Knitting Skeletons: Computer-Aided Design Tool for Shaping and Patterning of Knitted Garments (UIST 19) have received lots of media attention, including a recent interview from BBC. The story is also widely reported by TechCrunch7News BostonMashableFortuneVentureBeatEngadgetZDNetGeekMarket Research FinanceInteresting EngineeringFibre2Fashion, and MIT News.

08/07/2019
Paper accepted to UIST 2019

Alex's latest work Knitting Skeletons: A Computer-Aided Design Tool for Shaping and Patterning of Knitted Garments is officially accepted to UIST 2019. In this paper, Alex and Liane present a novel interactive system for simple garment composition and surface patterning. Both casual users and advanced users can benefit from their system. Check out these beautiful samples to explore the new possibility brought by their tool!

07/30/2019
Learning to fly in the news!

Jie's SIGGRAPH paper Learning to Fly: Computational Controller Design for Hybrid UAVs with Reinforcement Learning has been covered by media outlets including Engadget, UASWeekly, MashableVentureBeat, SlashGear, Robotics Business Review, Eletronics360, UberGizmo, DroneLife, Unmanned Aerial, Science Daily, and AI News in the past week. If you are at SIGGRAPH, come to room 151 and check out Jie's presentation today!

07/14/2019
One paper accepted to Science Advances

In our latest work published in Science Advances, our group presented an automated system that designs and 3-D prints complex robotic actuators which are optimized according to an enormous number of specifications. We demonstrate the system by fabricating actuators that show different black-and-white images at different angles. One of our actuators portrays a Vincent van Gogh portrait when laid flat and the famous Edvard Munch painting “The Scream” when tiled an angle. We also 3-D printed floating water lilies with petals equipped with arrays of actuators and hinges that fold up in response to magnetic fields run through conductive fluids.

The research paper Topology optimization and 3D printing of multimaterial magnetic actuators and displays was published in Science Advances last Friday, and MIT News covered our story on the same day.

05/29/2019
Paper published in Nature

Our latest work on human grasping "Learning the signatures of the human grasp using a scalable tactile glove" was published in Nature. In this paper, we use a scalable tactile glove and deep convolutional neural networks to show that sensors uniformly distributed over the hand can be used to identify individual objects, estimate their weight and explore the typical tactile patterns that emerge while grasping objects. Using a low-cost (about US$10) scalable tactile glove sensor array, we record a large-scale tactile dataset with 135,000 frames, each covering the full hand while interacting with 26 different objects. This set of interactions with different objects reveals the key correspondences between different regions of a human hand while it is manipulating objects. Insights from the tactile signatures of the human grasp—through the lens of an artificial analog of the natural mechanoreceptor network—can thus aid the future design of prosthetics, robot grasping tools, and human-robot interactions.

The paper was led by Subramanian Sundaram, who obtained his Ph.D. from our group in 2018 and continued this work after his graduation.

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