This research builds upon a vision-based reconstruction framework to augment robotic fabrication workflows, addressing their limitations in dynamically responding to the work environment. The study introduces an adaptive clay 3D printing workflow that integrates computer vision and graphics algorithms for scanning, registering, and reconstructing the robot's work envelope. This approach enables robotic clay 3D printing on indeterminate and complex surfaces, considering emergent material behaviors. A case study demonstrates the fabrication of interlocking components on reconfigurable sand formworks, highlighting the potential of this method in facilitating sustainable, customizable temporary formworks in robotic tasks. Collaborators: Emily K. Iseman, Benay Gürsoy
