Welcome to the new version of CaltechAUTHORS. Login is currently restricted to library staff. If you notice any issues, please email coda@library.caltech.edu
Published April 7, 2021 | Supplemental Material
Journal Article Open

Robotic surfaces with reversible, spatiotemporal control for shape morphing and object manipulation


Continuous and controlled shape morphing is essential for soft machines to conform, grasp, and move while interacting safely with their surroundings. Shape morphing can be achieved with two-dimensional (2D) sheets that reconfigure into target 3D geometries, for example, using stimuli-responsive materials. However, most existing solutions lack the ability to reprogram their shape, face limitations on attainable geometries, or have insufficient mechanical stiffness to manipulate objects. Here, we develop a soft, robotic surface that allows for large, reprogrammable, and pliable shape morphing into smooth 3D geometries. The robotic surface consists of a layered design composed of two active networks serving as artificial muscles, one passive network serving as a skeleton, and cover scales serving as an artificial skin. The active network consists of a grid of strips made of heat-responsive liquid crystal elastomers (LCEs) containing stretchable heating coils. The magnitude and speed of contraction of the LCEs can be controlled by varying the input electric currents. The 1D contraction of the LCE strips activates in-plane and out-of-plane deformations; these deformations are both necessary to transform a flat surface into arbitrary 3D geometries. We characterize the fundamental deformation response of the layers and derive a control scheme for actuation. We demonstrate that the robotic surface provides sufficient mechanical stiffness and stability to manipulate other objects. This approach has potential to address the needs of a range of applications beyond shape changes, such as human-robot interactions and reconfigurable electronics.

Additional Information

© 2021 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. This is an article distributed under the terms of the Science Journals Default License. Submitted 31 October 2020; Accepted 16 March 2021; Published 7 April 2021. We extend our appreciation to V. Lee for helping with the synthesis of LCEs and to R. Bai and P. Ermanni for helpful discussions. We acknowledge financial support from the U.S. NSF CSSI grant number 1835735 and from the Army Research Office (ARO) grant W911NF-17-1-0147. Travel funds to F.H. were provided by the financial aid office of ETH-Zürich. Author contributions: K.L. and C.D. designed the research. F.H. and K.L. performed all experiments and data postprocessing. K.L. conducted theoretical derivations and numerical simulations. C.D. supervised the project. All the authors participated in the analysis of the results and in the writing of the paper. The authors declare that they have no competing interests. Data and materials availability: All data needed to evaluate the conclusions in the paper are present in the paper or the Supplementary Materials. The code for numerical simulations has been deposited in the GitHub repository: https://github.com/Daraio-lab/RoboticSurface_SciRob_LiuK.

Attached Files

Supplemental Material - abf5116_Movie_S1.mp4

Supplemental Material - abf5116_Movie_S2.mp4

Supplemental Material - abf5116_Movie_S3.mp4

Supplemental Material - abf5116_Movie_S4.mp4

Supplemental Material - abf5116_SM.pdf


Files (170.1 MB)
Name Size Download all
40.7 MB Download
51.5 MB Download
25.3 MB Download
14.3 MB Preview Download
38.3 MB Download

Additional details

August 20, 2023
October 23, 2023