Growing and evolving 3D prints

Jon McCormack, Camilo Cruz Gambardella

Research output: Contribution to journalArticleResearchpeer-review

Abstract

Design-especially of physical objects-can be understood as creative acts solving practical problems. In this paper we describe a biologically-inspired developmental model as the basis of a generative form-finding system. Using local interactions between cells in a two-dimensional environment, then capturing the state of the system at every time step, complex three-dimensional (3D) forms can be generated by the system. Unlike previous systems, our method is capable of directly producing 3D printable objects, eliminating intermediate transformations and manual manipulation often necessary to ensure the 3D form is printable. We devise fitness measures for optimising 3D printability and aesthetic complexity and use a Covariance Matrix Adaptation Evolutionary Strategies algorithm (CMA-ES) to find 3D forms that are both aesthetically interesting and physically printable using fused deposition modelling printing techniques. We investigate the system’s capabilities by evolving and 3D printing objects at different levels of structural consistency, and assess the quality of the fitness measures presented to explore the design space of our generative system. We find that by evolving first for aesthetic complexity, then evolving for structural consistency until the form is ‘just printable’, gives the best results.

Original languageEnglish
Number of pages12
JournalIEEE Transactions on Evolutionary Computation
DOIs
Publication statusAccepted/In press - 6 Jul 2021

Keywords

  • 3D Printing
  • Aesthetics
  • Art
  • Biological system modeling
  • Complexity theory
  • Evolutionary Strategies.
  • Generative Art
  • Optimization
  • Solid modeling
  • Three-dimensional displays
  • Three-dimensional printing

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