TY - GEN
T1 - Metamodels for Rapid Analysis of Large Sets of Building Designs for Robotic Constructability
T2 - 18th Biennial International Conference on Engineering, Science, Construction, and Operations in Challenging Environments: Space Exploration, Utilization, Engineering, and Construction in Extreme Environments, Earth and Space 2022
AU - Muthumanickam, Naveen Kumar
AU - Duarte, José Pinto
AU - Nazarian, Shadi
AU - Bilén, Sven G.
N1 - Publisher Copyright:
© ASCE.
PY - 2023
Y1 - 2023
N2 - Disruptive robotic construction technologies such as additive deposition of cementitious materials like concrete (or “3D concrete printing”) require the synchronous operation of multiple pieces of equipment in the production setup. In such an environment, it is crucial to simulate the robotic motions (for toolpath clashes) and the cementitious material behavior (for toolpath failures) to ensure fail-proof constructability of the envisioned building geometry. However, toolpath clash detection requires 4D simulations of the production setup, which are computationally graphics intensive, whereas toolpath failure detection requires actual 3D printing of test parts from the geometry to identify areas prone to failure while 3D printing, which is physically tedious. Both these processes, being computationally and physically intensive, have largely curtailed designers from simulating and exploring large sets of design options with varying geometries and toolpath configurations. To overcome this and allow designers to explore large sets of design possibilities, this paper proposes two novel computational metamodels capable of performing robotic toolpath clash detection and failure detection with significantly reduced times than the earlier approaches. The developed metamodels were used to rapidly simulate large sets of building design options for robotic constructability in the NASA 3D-Printed Mars Habitat Challenge.
AB - Disruptive robotic construction technologies such as additive deposition of cementitious materials like concrete (or “3D concrete printing”) require the synchronous operation of multiple pieces of equipment in the production setup. In such an environment, it is crucial to simulate the robotic motions (for toolpath clashes) and the cementitious material behavior (for toolpath failures) to ensure fail-proof constructability of the envisioned building geometry. However, toolpath clash detection requires 4D simulations of the production setup, which are computationally graphics intensive, whereas toolpath failure detection requires actual 3D printing of test parts from the geometry to identify areas prone to failure while 3D printing, which is physically tedious. Both these processes, being computationally and physically intensive, have largely curtailed designers from simulating and exploring large sets of design options with varying geometries and toolpath configurations. To overcome this and allow designers to explore large sets of design possibilities, this paper proposes two novel computational metamodels capable of performing robotic toolpath clash detection and failure detection with significantly reduced times than the earlier approaches. The developed metamodels were used to rapidly simulate large sets of building design options for robotic constructability in the NASA 3D-Printed Mars Habitat Challenge.
UR - http://www.scopus.com/inward/record.url?scp=85146568069&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85146568069&partnerID=8YFLogxK
U2 - 10.1061/9780784484470.073
DO - 10.1061/9780784484470.073
M3 - Conference contribution
AN - SCOPUS:85146568069
T3 - Earth and Space 2022: Space Exploration, Utilization, Engineering, and Construction in Extreme Environments - Selected Papers from the 18th Biennial International Conference on Engineering, Science, Construction, and Operations in Challenging Environments
SP - 871
EP - 884
BT - Earth and Space 2022
A2 - Dreyer, Christopher B.
A2 - Littell, Justin
PB - American Society of Civil Engineers (ASCE)
Y2 - 25 April 2022 through 28 April 2022
ER -