MEAM Ph.D. Thesis Defense: “Leveraging Impedance-Related Properties for Free Self-Sensing in Actuators for Compact Robots”

Robotic systems, particularly at small scales, require efficient actuation and sensing solutions that maintain compactness. We are interested in systems where sensing and actuation are seamlessly integrated, specifically using impedance-related properties—such as electrical resistance, induced electromotive force (emf), and inductance— for free self-sensing in actuators without additional sensors. We explore three main example applications: (1) Resistance-based sensing in I-cord knitted shape memory alloy (SMA) actuators enables real-time strain estimation, allowing direct feedback for robotic motion, (2) Induced emf sensing in custom linear solenoid actuators provides contact and velocity feedback, demonstrated in applications such as bistable origami grippers and artificial facial muscle devices for facial reanimation surgery, and (3) Inductance-based sensing further enables position and flow monitoring in active valve systems for bidirectional swimming of underwater swimmer robots, offering a self-contained alternative to external instrumentation. This thesis presents the theoretical foundations, experimental validation, and real-world robotic demonstrations of these sensing approaches. By embedding sensing directly into actuators, this work advances the development of compact and robust robotic systems with potential applications in origami-inspired soft robots, bio-inspired robots, and medical implant devices.