Getting a Grip: in Materio Evolution of Membrane Morphology for Soft Robotic Jamming Grippers
David Howard, Jack O'Connor, Jordan Letchford, James Brett, Therese, Joseph, Sophia Lin, Daniel Furby, Gary W. Delaney

TL;DR
This paper introduces an innovative method combining multi-material 3D printing and evolutionary algorithms to optimize membrane morphology in granular jamming grippers, significantly enhancing their gripping performance.
Contribution
It is the first study to optimize membrane morphology for granular jamming grippers using a materio approach with evolutionary algorithms and 3D printing.
Findings
Membrane morphology significantly affects gripper performance.
Optimized designs outperform standard morphologies across various objects.
Evolutionary optimization effectively explores complex design space.
Abstract
The application of granular jamming in soft robotics is a recent and promising new technology offer exciting possibilities for creating higher performance robotic devices. Granular jamming is achieved via the application of a vacuum pressure inside a membrane containing particulate matter, and is particularly interesting from a design perspective, as a myriad of design parameters can potentially be exploited to induce a diverse variety of useful behaviours. To date, the effect of variables such as grain shape and size, as well as membrane material, have been studied as a means of inducing bespoke gripping performance, however the other main contributing factor, membrane morphology, has not been studied due to its particular complexities in both accurate modelling and fabrication. This research presents the first study that optimises membrane morphology for granular jamming grippers,…
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Taxonomy
TopicsSoft Robotics and Applications · Modular Robots and Swarm Intelligence · Cellular Mechanics and Interactions
