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Publications

Highlights of cutting-edge work that has been performed leveraging Inkbit's technology.

Vision-controlled jetting for composite systems and robots

Authors

Thomas J. K. Buchner, Simon Rogler, Stefan Weirich, Yannick Armati, Barnabas Gavin Cangan, Javier Ramos, Scott T. Twiddy, Davide M. Marini, Aaron Weber, Desai Chen, Greg Ellson, Joshua Jacob, Walter Zengerle, Dmitriy Katalichenko, Chetan Keny, Wojciech Matusik & Robert K. Katzschmann

Abstract

Introduces Vision-Controlled Jetting (VCJ), an inkjet deposition process for creating complex composite systems and robots. A scanning system captures the 3D print geometry and enables a digital feedback loop that eliminates the need for mechanical planarizers. This contactless process allows the use of continuously curing chemistries and a broader range of materials, including tough epoxy and soft thiol-ene, leading to multi-material parts with high resolution and superior properties like increased solvent and UV resistance.

Dense, Interlocking-Free and Scalable Spectral Packing of Generic 3D Objects

Authors

Qiaodong Cui, Victor Rong, Desai Chen, Wojciech Matusik

Abstract

Introduces the Scalable Spectral Packing (SSP) algorithm to solve the NP-hard problem of densely packing 3D objects into a container for manufacturing (like 3D printing). The method uses a discrete voxel representation and formulates collisions as correlations of functions computed efficiently using the Fast Fourier Transform (FFT). Crucially, the method ensures the packing is "interlocking-free," meaning all objects can be removed without deformation or breakage. It achieves state-of-the-art performance in both density and speed.

Controlling diverse robots by inferring Jacobian fields with deep networks

Authors

Sizhe Lester Li, Annan Zhang, Boyuan Chen, Hanna Matusik, Chao Liu, Daniela Rus & Vincent Sitzmann

Abstract

Introduces Neural Jacobian Fields, an architecture using deep neural networks to learn to model and control diverse robots from vision alone. The method maps a video stream to a visuomotor Jacobian Field the sensitivity of all 3D points to the robot's actuators. It makes no assumptions about the robot's materials, actuation, or sensing, requiring only a single camera and training by observing random commands. This enables accurate closed-loop control for systems that are traditionally hard to model, such as multi-material and soft robots, potentially lowering the barrier to robotic automation.

Scaling law for intrinsic fracture energy of diverse stretchable networks

Authors

Shu Wang, Qiaodong Cui, Wojciech Matusik, Bolei Deng, Xuanhe Zhao

Abstract

Reveals a universal scaling law that links strand mechanics and connectivity to predict the intrinsic fracture energy of diverse stretchable networks. This law establishes a physical basis for fracture resistance, showing that Gamma is independent of the energy to rupture a strand but depends on the strand rupture force, breaking length, and connectivity. The law provides a framework for fabricating and designing tougher materials across various topologies, dimensionalities, and length scales, from nanoscale polymers to macroscale architected materials.

Directly 3D printed, pneumatically actuated multi-material robotic hand

Authors

Hanna Matusik, Chao Liu, Daniela Rus

Abstract

Presents a fully 3D-printed, multi-material robotic hand that is pneumatically actuated (controlled by air pressure). This demonstrates the capability of advanced fabrication techniques to create integrated, soft robotic manipulators with many degrees of freedom. The authors have worked on bio-inspired hands that combine soft and rigid elements to achieve high dexterity and sensitivity.

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