Dec 16, 2016 | By Benedict

Cornell researchers have used a 3D printer and four-step soft lithography to create a soft robotic hand that can feel surfaces just like a human. Stretchable optical waveguides act as curvature, elongation, and force sensors in the 3D printed hand.

Touching, feeling, and grasping are things we start doing from the day we are born. That makes them easy to think about in a loose sense, but also difficult to truly put our finger on. How do we experience the sensation of touch? How could we replicate that sensation in a nonhuman entity? Is touch an internal or external sensation? A research team at Cornell University, led by assistant professor of mechanical and aerospace engineering Robert Shepherd, is concerned with these very questions, and has used 3D printing to try and answer them.

While most robots achieve grasping and tactile sensing through motors, Shepherd and co have devised a soft robotic hand, built using 3D printed molds, which uses the external tips of its fingers to gather information while actually “feeling” the sensation internally—much like humans do. Doctoral student Huichan Zhao is lead author of the paper, “Optoelectronically Innervated Soft Prosthetic Hand via Stretchable Optical Waveguides,” which is featured in the debut edition of Science Robotics.

“Most robots today have sensors on the outside of the body that detect things from the surface,” Zhao said. “Our sensors are integrated within the body, so they can actually detect forces being transmitted through the thickness of the robot, a lot like we and all organisms do when we feel pain, for example.”

The researchers created a clever system that is able to feel its surroundings through light. As the soft robotic hand deforms, more light is lost through the core, and that loss of light is detected by a photodiode. The team employed a four-step soft lithography process to produce the core (which light passes through), and the cladding (the outer surface of the waveguide), which also houses an LED and the photodiode.

In addition to soft lithography, 3D printing also plays an important role in the process: “We 3D print the molds using a PolyJet printer (Objet30) for our optical waveguides,” the researchers explain in the paper. “This fabrication process generates a surface roughness of 6 nm between the core and cladding. This relatively rough interface causes scattering and thus more loss of propagation; however, the design freedom of 3D printing allows for complex sensor shapes.”

Optical waveguides such as those used by the Cornell researchers have been in use since the early 1970s for tactile, position, and acoustic sensing, amongst other things. Making these devices used to be difficult, but the rise of soft lithography and 3D printing over the last two decades has given rise to the rapid production of elastomeric sensors for soft robotic applications.

The optoelectronic hand, made from 3D printed molds, has been able to perform a variety of tasks, such as grasping and probing for both shape and texture. Interestingly (for both scientists and food lovers), the hand was able to scan three tomatoes and determine, by softness, which was the ripest.

Although able to process data just like a human hand, it is essentially the presence or absence of light which enables the device to understand the surfaces it touches. “If no light was lost when we bend the prosthesis, we wouldn’t get any information about the state of the sensor,” Shepherd said. “The amount of loss is dependent on how it’s bent.”

The unusual research project, which involved 3D printing, soft lithography, and the use of optical waveguides, was supported by a grant from Air Force Office of Scientific Research, and made use of the Cornell NanoScale Science and Technology Facility and the Cornell Center for Materials Research, both of which are supported by the National Science Foundation.

 

 

Posted in 3D Printing Application

 

 

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