Nerve-like mesh could give robots a sense of touch more delicate than SKIN on the human back, study claims

  • The material is made of flexible polyurethane threaded with optical fibres
  • Sensors along the fibres detect deformation through changes in the flow of light
  • The concept could be used to form a type of flesh for future robot designs
  • Such robots could be used for manufacturing, healthcare and other applications

A synthetic mesh could give robots a sense of touch that is delicate as the skin on out backs, researchers have claimed.

The material forms a linked sensory network similar to that of a biological nervous system — one that could help robots feel their interactions with the environment. 

The lattice is made of flexible polyurethane that contains stretchable optical fibres with sensors than can detect how the fibres are being deformed.

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A synthetic mesh could give robots a sense of touch that is delicate as the skin on out backs, researchers have claimed

A synthetic mesh could give robots a sense of touch that is delicate as the skin on out backs, researchers have claimed

The device — a sort-of stretchable optical lace — was developed by roboticists Patricia Xu and Rob Shepherd of Cornell University and colleagues.

‘We want to have a way to measure stresses and strains for highly deformable objects, and we want to do it using the hardware itself, not vision,’ said Professor Shepherd.

‘A good way to think about it is from a biological perspective.’ 

‘A blind person can still feel because they have sensors in their fingers that deform when their finger deforms. Robots don’t have that right now.’ 

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To create a material that can detect deformations, the researchers created a flexible lattice — 3D printed out of polyurethane — into which was threaded stretchable optical fibres containing more than a dozen sensors.

When the lattice is pressed at various points, the sensors were able to pinpoint the corresponding changes in the flow of photons through the optical fibres. 

‘When the structure deforms, you have contact between the input line and the output lines, and the light jumps into these output loops in the structure, so you can tell where the contact is happening,’ Ms Xu said.

‘The intensity of this determines the intensity of the deformation itself.’

Although the lace is not as sensitive as human fingertips — which have a high concentration of nerve receptors  — the material is still more sensitive to touch than the skin found on our backs.

The material forms a linked sensory network similar to that of a biological nervous system — one that could help robots feel their interactions with the environment

The material forms a linked sensory network similar to that of a biological nervous system — one that could help robots feel their interactions with the environment

In a practical application, the optical lace would not serve as a skin coating for robots, but would act more like the flesh itself,’ Professor Shepherd said.

Robots constructed with the material would be suited for various tasks — from manufacturing to uses in the health care industry — specifically beginning- and end-of-life care, the researchers said.

The team have also launched a startup company which hopes, given that the material is completely washable, to commercialise the sensors into garments that can measure the wearer’s shape and movements for augmented reality training.

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The full findings of the study were published in the journal Science Robotics

WILL YOUR JOB BE TAKEN BY A ROBOT?

A report in November 2017 suggested that physical jobs in predictable environments, including machine-operators and fast-food workers, are the most likely to be replaced by robots.

Management consultancy firm McKinsey, based in New York, focused on the amount of jobs that would be lost to automation, and what professions were most at risk.

The report said collecting and processing data are two other categories of activities that increasingly can be done better and faster with machines. 

This could displace large amounts of labour – for instance, in mortgages, paralegal work, accounting, and back-office transaction processing.

Conversely, jobs in unpredictable environments are least are risk.

The report added: ‘Occupations such as gardeners, plumbers, or providers of child- and eldercare – will also generally see less automation by 2030, because they are technically difficult to automate and often command relatively lower wages, which makes automation a less attractive business proposition.’

 



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