Optical lace offers soft robots a tactile sensor network

September 12, 2019 //By Julien Happich
soft robots
Using a 3D-printed elastomer structure with stretchable embedded light guides, researchers from Cornell University were able to develop what amounts to a distributed, volumetric tactile sensing network that could enable soft robots to interact with their environment with a high tactile resolution.

Their article “Optical lace for synthetic afferent neural networks” published in Science Robotics describes various experiments using a 3D-printer to integrate arbitrary 3D grids of soft stretchable light guides throughout the volume of a soft deformable scaffold. Some of the light guides are considered as input cores (receiving light from a LED) while networks of neighbouring light guides act as output cores, only carrying leaked light from the input cores upon deformation.

Schematic cross section showing the light guides with a
close-up of the mechanoreceptor.

By optically measuring the coupling interactions (all the light power outputs), they were able to sense spatially continuous deformations and localize them with sub-millimetre accuracy, detecting forces as low as 0.3 Newton. In one experiment, they were able to simultaneously locate multiple finger presses and monitor the volumetric structural deformation of a soft scaffold just by measuring the coupling interactions within the optical lace. Here they used 1.5mm diameter polyurethane light guides for the input cores and 1mm diameter light guides for the output cores, loosely held in place into lattice-work channels designed within the scaffold structure and spaced apart by small air gaps in the resting state. For any given finger press, the touch position could be calculated using the ratio of intensities in the neighbouring output light guides.

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