Granular Jamming

Granular jamming leverages the transition of granular materials from a fluid-like to a solid-like state under applied pressure to create adaptable and robust robotic grippers and actuators. Current research focuses on optimizing gripper design through material selection, membrane morphology (including 3D-printed structures), and active control mechanisms like vibration-based fluidization, often employing machine learning for real-time object tracking and control. This field is significant for its potential to create soft robots with enhanced dexterity, adaptability, and gripping strength for applications ranging from minimally invasive surgery to extraterrestrial exploration.