Material in the Loop Fabrication (2023-07)¶

The limitations of the robotic fabrication workflows in seeing, sensing, and responding to the changes in the work envelope typically impose a “unidirectional information flow.” To overcome these challenges, we previously explored ways to augment the robotic fabrication by using vision-based reconstruction frameworks to digitally capture the work envelope and inform toolpath generation accordingly [9]. Building upon this framework, we present an adaptive clay 3D printing workflow that employs computer vision and computer graphics algorithms to scan, register, and accurately reconstruct the robot’s work envelope. This allows the robotic clay 3D printing operations to be carried out on indeterminate (unknown) and complex surfaces and enables accounting for emergent material behaviors in consequent robotic tasks. We explore the applicability of this vision-based framework through a case study in which we fabricated interlocking components by robotically 3D printing clay on re-configurable sand formworks. Within this workflow, the moldable sand mixture is shaped by the robot into reusable and temporary formwork, which acts as a supporting structure during the fabrication and firing of the clay panels. Based on our early findings, We postulate that this approach can help facilitate the integration of such temporary formworks in robotic fabrication tasks as a more sustainable and customizable alternative.