| id |
acadia16_12 |
| authors |
Gerber, David Jason; Pantazis, Evangelos |
| year |
2016 |
| title |
A Multi-Agent System for Facade Design: A design methodology for Design Exploration, Analysis and Simulated Robotic Fabrication |
| doi |
https://doi.org/10.52842/conf.acadia.2016.012
|
| source |
ACADIA // 2016: POSTHUMAN FRONTIERS: Data, Designers, and Cognitive Machines [Proceedings of the 36th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) ISBN 978-0-692-77095-5] Ann Arbor 27-29 October, 2016, pp. 12-23 |
| summary |
For contemporary design practices, there still remains a disconnect between design tools used for early stage design exploration and performance analysis, and those used for fabrication and construction of complex tectonic architectural systems. The research brings forward downstream fabrication constraints into the up-stream design exploration and design decision making. This paper addresses the issues of developing an integrated digital design work-flow and details a research framework for the incorporation of environmental performance into a robotic fabrication for early stage design exploration and generation of intricate and complex alternative façade designs. The method allows the user to import a design surface, define design parameters, set a number of environmental performance objectives, and then simulate and select a robotic construction strategy. Based on these inputs, design alternatives are generated and evaluated in terms of their performance criteria in consideration of their robotically simulated constructability. In order to validate the proposed framework, an experimental case study of office building façade designs that are generatively created from a multi-agent system for design methodology is design explored and evaluated. Initial results define a heuristic function for improving simulated robotic constructability and illustrate the functionality of our prototype. Project limitations and future research steps are then discussed. |
| keywords |
generative design, multi-objective design optimization, robotic fabrication, simulation, design performance, design decision making |
| series |
ACADIA |
| type |
paper |
| email |
|
| full text |
 file.pdf (951,723 bytes) |
| references |
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