This research develops soft robots using liquid crystal elastomers that act as artificial muscles. By designing materials at the molecular level and 3D printing them into responsive structures, researchers can create flexible robots that move like animals. These soft robots could navigate tight spaces during search-and-rescue missions after disasters.

This thesis introduces Armando, a low-cost soft robotic gripper with proprioceptive sensing using a single flexible capacitive sensor and neural-network decoding. Achieving 99% accuracy, Armando enables precise finger-position estimation for applications in prosthetics, assistive care, and disaster response, advancing accessible tactile robotics inspired by human touch.