Fabric Jamming

Fabric jamming, the controlled stiffening of flexible materials by altering their internal structure, is being explored for applications ranging from soft robotics to anti-jamming technologies. Current research focuses on optimizing jamming parameters (e.g., fiber density, number) to achieve desired stiffness variations, often employing machine learning models like convolutional neural networks and Bayesian networks for detection and control. This work is significant for advancing the design of adaptable robots and developing robust countermeasures against signal jamming in wireless communication systems, impacting fields from minimally invasive surgery to secure drone operation.