Robot with a Human Touch

A soft robot has been created that can feel its surroundings internally, much like humans do.

Using stretchable optical waveguides as curvature, elongation and force sensors in a soft robotic hand, researchers at Cornell University have overcome the hindrances often associated with using motorized means for sensing.

Capabilities of the hand. (a) Holding a coffee mug; (b and c) grasping a tomato with the palm facing down (b) and the palm facing up (c); (d) shaking a human hand; (e) lateral scanning over surfaces to detect roughness and shape; and (f) probing the softness of a soft sponge. Courtesy of Melissa Osgood.

"Most robots today have sensors on the outside of the body that detect things from the surface," said doctoral student Huichan Zhao. "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."

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.

The research group led by Robert Shepherd, assistant professor of mechanical and aerospace engineering and principal investigator of Organic Robotics, 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 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," Shepherd said. "The amount of loss is dependent on how it's bent."

The group used its optoelectronic prosthesis to perform a variety of tasks, including grasping and probing for both shape and texture. Most notably, the hand was able to scan three tomatoes and determine, by softness, which was the ripest.

The study is featured in the journal Science Robotics (DOI: 10.1126/scirobotics.aai7529).