Multiplanar Robotic Tube Bending
Gregory Thomas Spaw, Lee-Su Huang, Ammar Kalo
United Arab Emirates, United States of America
The work showcased here is a process-based design research project that reimagines traditional manual tube bending techniques with the precision and efficiency of digital formative fabrication. Leveraging the positional accuracy of industrial robots using custom tools to bend and interweave metal tubes in geometrically complex and spatially precise configurations, the research follows a lineage of projects1&2 exploring the application of robotic bending of linear elements, primarily in solid-core rod form3. While other precedents highlight the use of traditional bent pipe methods4-6, and achieve the scale and capacity to be inhabitable, they are typically realized through use of elaborate jigs, large fabrication spaces, and intense manual labor. This investigation attempts to integrate the material efficiency and scalar advantages of tubes with the precision and repeatability of industrial robot-based formative fabrication. Utilizing a Kuka six-axis industrial robot and a two-axis positioner as a turntable, a custom 3d-printed gripper with pneumatic control enables gripping, rotation, and feeding into the external axis with a center die and an outer roller forming pin. The computational workflow uses a Grasshopper7 parametric definition to reference simple polyline geometry and fillets the corners with a fixed diameter that corresponds to the static bending die. The filleted curve geometry is analyzed and broken down into straight sections which correspond to feed distance, and curved sections which correspond to bend angles. The geometry is parsed and sequenced into Kuka KRL8 code from Kuka|PRC for robot movement simulation, collision detection, as well as external axis instructions for the turntable and gripper. As an on-going series of explorations meant to gradually scale up in size and complexity, the research uncovers possibilities for bundled and interwoven tubular structures that represent a paradigm shift in how tubular structures might be designed and fabricated in the future with minimal falsework and scaffolding. Endnotes Smigielska, Maria. Application of Machine Learning Within the Integrative Design and Fabrication of Robotic Rod Bending Processes, Humanizing Digital Reality, (Singapore:Springer 2017), 523-536. MacDowell, Parke, Diana Tomova, “Robotic Rod-bending: Digital Drawing in Physical Space,” in Integration through Computation Proceedings, ACADIA 2011, ed. Joshua M Taron (Calgary:ACADIA 2011), 132-137. Maxwell, Iain, David Pigram, and Wes McGee, “ The Novel Stones of Venice: The Marching Cube Algorithm as a Strategy for Managing Mass-Customisation,” in Adaptive Architecture Proceedings, ACADIA 2013, ed. Philip Beesley, Michael Stacey, and Omar Khan (Cambridge: Riverside Architectural Press 2013), 311-318. Oyler, Dwayne, and Jenny Wu, “Live Wire,” oylerwu, Accessed October 20, 2021, https://www.oylerwu.com/live-wire. “La Cage Aux Folles,” WTARCH, Accessed October 20, 2021, https://www.wtarch.com/la-cage-aux-folles. Johnson, Jason Kelly, and Nataly Gattegno, “Lightweave by FUTUREFORMS,” FUTUREFORMS, Accessed October 20, 2021, https://www.futureforms.us/lightweave. McNeel, Rhinoceros+Grasshopper V. 7.7.21160.5001, Robert McNeel & Associates, PC, 2020. Braumann, Johannes, Kuka|prc V.2020-01-24, Association for Robots in Architecture, PC, 2020.