Robotics Thesis Proposal
- Gates Hillman Centers
- ERIC MARKVICKA
- Ph.D. Student
- Robotics Institute
- Carnegie Mellon University
Soft-Matter Robotic Materials
Soft machines and electronics are key components for emerging applications in wearable biomonitoring, human-machine interaction, and soft robotics. In contrast to conventional machines and electronics, soft-matter technologies provide a method for replicating these traditionally rigid devices using intrinsically soft materials that exhibit properties similar to soft biological tissue. This provides a path forward for creating devices that are inherently safe and can intimately interact with the human body. While promising, widespread use is limited by the lack of robust fabrication methods, tight integration of computation, sensing, and actuation, and the ability for these devices to operate in complex and unstructured environments outside of the laboratory. Of particular importance is the development of soft and stretchable circuitry that can function as ”artificial” skin and nervous tissue for use in wearable and robotic systems.
In this work, several novel fabrication methods are presented for creating hybrid electronic skins that tightly integrate advanced integrated circuits (ICs) with soft and flexible mediums enabling intimate interaction with humans and existing robotic platforms. These methods provide an approach for creating highly customizable sensor skins that overcome limitations in alignment and electrical and mechanical interfaces between the rigid ICs and soft polymers and fluids. To validate their practical applicability, the hybrid electronic skins were incorporated into soft, body-mounted wearable electronics for biomonitoring and human-machine interaction.
This research also explored the creation of soft multifunctional elastomers with enhanced electrical properties. This was accomplished by incorporating liquid-metal (LM) microdroplets into hyperelastic materials to create hybrid composites that exhibit the elastic properties of soft rubber. The integration of LM microdroplets in a soft, highly elastic silicone elastomer increased the dielectric constant by over 400%. When integrated with a stiffer silicone elastomer, application of sufficient local pressure causes the droplets to rupture and form a continuous LM network, enabling soft circuits to be created. This materials architecture and framework has a high volumetric electrical conductivity, exhibits a minimal change in resistance versus stretch, and is capable of autonomous self-healing, enabling these soft-matter devices to operate in complex and unstructured environments. In contrast to previous efforts, self-healing is achieved without loss of conductivity, manual intervention, changes to the environmental conditions (e.g. temperature, humidity), use of external energy sources, or redundant electronics. The material is capable of undergoing extreme and repeated mechanical damage, including cutting, puncturing, and complete removal of material from the circuit interconnects without loss of conductivity. Demonstrations on a soft robot testbed suggest that this material can function as a self-repairing artificial nervous tissue that allows for highly robust, damage resilient functionality.
Carmel Majidi (Chair)
Metin Sitti (Max Planck Institute)