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Abstract Elephant trunks are capable of complex, multimodal deformations, allowing them to perform task‐oriented high‐degree‐of‐freedom (DOF) movements pertinent to the field of soft actuators. Despite recent advances, most soft actuators can only achieve one or two deformation modes, limiting their motion range and applications. Inspired by the elephant trunk musculature, a liquid crystal elastomer (LCE)‐based multi‐fiber design strategy is proposed for soft robotic arms in which a discrete number of artificial muscle fibers can be selectively actuated, achieving multimodal deformations and transitions between modes for continuous movements. Through experiments, finite element analysis (FEA), and a theoretical model, the influence of LCE fiber design on the achievable deformations, movements, and reachability of trunk‐inspired robotic arms is studied. Fiber geometry is parametrically investigated for 2‐fiber robotic arms and the tilting and bending of these arms is characterized. A 3‐fiber robotic arm is additionally studied with a simplified fiber arrangement analogous to that of an actual elephant trunk. The remarkably broad range of deformations and the reachability of the arm are discussed, alongside transitions between deformation modes for functional movements. It is anticipated that this design and actuation strategy will serve as a robust method to realize high‐DOF soft actuators for various engineering applications.
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Spatiotemporally Controlled Soft Robotics with Optically Responsive Liquid Crystal Elastomers
Light‐responsive materials enable the development of soft robots that are controlled remotely in 3D space and time without the need for cumbersome wires, onboard batteries, or altering the local environment. Azobenzene liquid crystal polymer networks are one such material that can move and deform in response to light actuation. Previous works have demonstrated azo‐based soft robotic grippers and transporters that are remotely powered by light. However, highly adaptive, automated spatiotemporal optical control over these materials has not yet been realized. Herein, a system for an azobenzene liquid crystal elastomer soft robotic arm is created by dynamically patterning light for independently maneuverable joints. The nonlinear material response to optical actuation is characterized, and the broad actuation space is explored with diverse arm configurations. A neural network is trained on the arm configurations and corresponding laser pattern to automate the pattern generation for a desired configuration. Finally, the azobenzene liquid crystal elastomer arm demonstrates complex targeted motion, marking an important step toward optically actuated soft robotics with applications ranging from optomechanics to biomedical tools.
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- Award ID(s):
- 2240106
- PAR ID:
- 10583242
- Publisher / Repository:
- Wiley Blackwell (John Wiley & Sons)
- Date Published:
- Journal Name:
- Advanced Intelligent Systems
- Volume:
- 7
- Issue:
- 6
- ISSN:
- 2640-4567
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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