New, soft robotic hand can 'feel' its surroundings

Scientists have developed a soft robotic hand that can feel its surroundings internally, just as humans, and perform tasks like picking out ripe tomatoes.
Most robots achieve grasping and tactile sensing through motorised means, which can be excessively bulky and rigid.
Researchers from Cornell University in the US, led by assistant professor Robert Shepherd, showed how stretchable optical waveguides can act as curvature, elongation and force sensors in a soft robotic hand.
"Most robots today have sensors on the outside of the body that detect things from the surface," said Huichan Zhao, doctoral student at Cornell.
"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," Zhao said.

Optical waveguides have been in use since the early 1970s for numerous sensing functions, including tactile, position and acoustic.

Fabrication was originally a complicated process, but the advent over the last 20 years of soft lithography and 3D printing has led to development of elastomeric sensors that are easily produced and incorporated into a soft robotic application.
Researchers employed a four-step soft lithography process to produce the core (through which light propagates), and the cladding (outer surface of the waveguide), which also houses the LED (light-emitting diode) and the photodiode.
The more the prosthetic hand deforms, the more light is lost through the core.

That variable loss of light, as detected by the photodiode, is what allows the prosthesis to "sense" its surroundings.
"If no light was lost when we bend the prosthesis, we wouldn't get any information about the state of the sensor. The amount of loss is dependent on how it's bent," Shepherd said.
The group used its optoelectronic prosthesis to perform a variety of tasks, including grasping and probing for both shape and texture.
The hand was able to scan three tomatoes and determine, by softness, which was the ripest.
The research was published in the journal Science Robotics.