PhD Thesis Proposal
Carnegie Mellon University
11:00 am - 12:00 pm
The increasing prevalence of wearable technology in our daily lives has created a demand for safe and robust sensing skins. Largely inspired by human skin, the ultimate goal of electronic skins is to measure diverse sensory information, conform to surfaces, and avoid interfering with the natural mechanics of the host or user. These demands require an alternative approach to conventional sensing electronics, which are typically planar and rigid. Soft sensors fill this gap by employing materials and substrates that mimic the mechanical properties of living tissues. Their natural compliance makes soft sensors well-suited for a variety of robotic applications including object manipulation, tactile sensing, and human-robot interaction.
However, stretchable sensors face unique challenges that require the development of novel fabrication techniques and methods to handle the non-linear characteristics of soft materials. For these reasons, soft sensors have been largely limited to pressure and strain sensing. These challenges not only restrict their functionality, but also make it difficult for soft sensors to compete with commercially-available rigid sensors. This work introduces several additional soft sensing approaches to enable further progress and diversity in soft sensor applications.
First, a biohybrid pneumatic gripper was designed to take advantage of the inherent material compatibility between synthetic biology and soft robotics. Chemical signals in the environment are expressed by the development of fluorescent proteins, which are detected by on-board opto-electronics in the gripper’s strain-limiting layer. This implementation supports the integration of biological cells and soft robotic materials for advanced chemical sensing. Second, I scale up a technique to fabricate larger and more complex hybrid microelectronic skins with commercial IC chips. The combination of stretchable substrate, liquid-metal traces, and IC chips achieves soft sensing skins with on-board processing, communication, and MEMS sensors for the first time. Lastly, the proposed work introduces a novel magnetic elastomer composite for deformation sensing. Preliminary characterization, theory, and results are reported. The proposed work focuses on optimizing the fabrication process, characterizing different types of deformation, and developing a fully-soft system demonstration. Taking inspiration from many fields, I aim to bridge robotics with soft sensing technologies to advance the development of complex, robust, and soft interfaces and systems.
Thesis Committee Members:
Carmel Majidi, Chair
Ellen Roche, Massachusetts Institute of Technology