A nonlinear optimization method for large shape morphing in 3D printed pneumatic lattice structures

Abstract

Shape morphing has been increasingly investigated as a solution to increase the functionality and efficiency of structures. The main criteria to assess the quality of a shape morphing structure in this paper are: accuracy of deformation and range and number of achievable target shapes. The lightweight lattice structures used in this work inherently address the first criteria. The focus of this work is to address accuracy and range by developing a nonlinear optimization method that can handle large shape changes and a variety of target shapes for 2D and 3D overdeterminate lattice structures. The accuracy and deformation range of the method are verified numerically using Finite Element Analysis (FEA) and experimentally through a modular, 3D printed pneumatic lattice toolkit. The method is shown to replicate desired target shapes with a minimum accuracy of 80.4% for case studies in 2D and 69.1% in 3D. The simulation and the experimental results replicate results from the actuator placement optimization with a minimum accuracy of 92.3% and 76.2% respectively in 2D, and 88.2% and 69.6% in 3D. The impact of varying the size and degree of static overdeterminacy of a structure on its deformation range is evaluated. The proposed optimization method provides designers with more design freedom in terms of the structure type, target shape, and deformation range than shown in similar publications.