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Will Optical Lace be Successful in Providing Robots a Human Touch?

Enterprise Technology Review | Tuesday, October 01, 2019

A new stretchable material that builds a connected sensory network akin to a biological nervous system can allow the soft robots to interact with the environment and perform actions accordingly.

FREMONT, CA: A new sensor having optical fibers have come up in the market, which is embedded in a 3D-printed elastomer. This sensor can make for a sensory network that enables the robots to touch and sense the way they communicate with their environment. This stretchable optical lace is distributed throughout the entire body of a robot, like a biological nervous system. It has the ability to localize sub-millimeter positional accuracy with applied deformations and sub-Newton force resolution (0.3N).

The researchers have found it difficult to wire the nerve-like networks throughout the robot's body. Recently, an optical lace has been created by a team of mechanical engineers led by Rob Shepherd and Particia Xu of Cornell University, U.S. The optical lace comprises optical fibers that contain dozen-plus mechanosensors entrenched in a 3D- printed elastomer connected to a light-emitting diode that can resolve this problem.

Optical guides can detect the deformation level

On pressing the lattice structure, the struts in the 3D lattice experience the deformation level, which is detected by the optical guides by measuring the intensity and light loss location in the optical fibers through coupling. The deformation's intensity is determined by the intensity of the coupled light.

According to the researchers, the distribution of the optical lace throughout the robot's body enables the robot to be both exteroceptive and proprioceptive. The optical lace system resembles the biological nervous system, in which an individual's skin is embedded with mechanoreceptors at various locations.

The sensors distributed by optical lace report the position and magnitude of deformations to a computer. Further, the location is encoded in the sensor's position, and the intensity of light coupled encodes the deformation's magnitude.

Secured communication with people

In robots, the externally caused deformation, i.e., exteroception can be measured by placing the sensors close to the surface in the right orientation, and internal deformation (proprioception) can be measured by placing the sensors deep inside the structure.

The integration of these sensor networks into robots will enable them to interact safely with the people. It will also allow them to help the elderly and disabled.

Softer than cold, hard cyborgs

Cyborgs can be used in manufacturing industries. The ability of the robots to touch and feel can improve accuracy.

The work of mechanical engineers, here, which is given in detail in Science Robotics and supported by the Air Force Office of Scientific Research and the Office of Naval Research, reveals that the researchers hired physical models for translating sensor signals into deformation states.

In the future, scientists and researchers are trying to make more extensive networks and produce more intricate deformations. Machine learning can also contribute to creating these more sophisticated models and identify distortions such as bending and twisting.