̽��ֱ�� of Cambridge - David Hardman

Robot trained to read braille at twice the speed of humans

sc604 — Mon, 29 Jan 2024 06:04:52 +0000

̽��ֱ��research team, from the ̽��ֱ�� of Cambridge, used machine learning algorithms to teach a robotic sensor to quickly slide over lines of braille text. ̽��ֱ��robot was able to read the braille at 315 words per minute at close to 90% accuracy.

Although the robot braille reader was not developed as an assistive technology, the researchers say the high sensitivity required to read braille makes it an ideal test in the development of robot hands or prosthetics with comparable sensitivity to human fingertips. ̽��ֱ��results are reported in the journal IEEE Robotics and Automation Letters.

Human fingertips are remarkably sensitive and help us gather information about the world around us. Our fingertips can detect tiny changes in the texture of a material or help us know how much force to use when grasping an object: for example, picking up an egg without breaking it or a bowling ball without dropping it.

Reproducing that level of sensitivity in a robotic hand, in an energy-efficient way, is a big engineering challenge. In Professor Fumiya Iida’s lab in Cambridge’s Department of Engineering, researchers are developing solutions to this and other skills that humans find easy, but robots find difficult.

“ ̽��ֱ��softness of human fingertips is one of the reasons we’re able to grip things with the right amount of pressure,” said Parth Potdar from Cambridge’s Department of Engineering and an undergraduate at Pembroke College, the paper’s first author. “For robotics, softness is a useful characteristic, but you also need lots of sensor information, and it’s tricky to have both at once, especially when dealing with flexible or deformable surfaces.”

Braille is an ideal test for a robot ‘fingertip’ as reading it requires high sensitivity, since the dots in each representative letter pattern are so close together. ̽��ֱ��researchers used an off-the-shelf sensor to develop a robotic braille reader that more accurately replicates human reading behaviour.

“There are existing robotic braille readers, but they only read one letter at a time, which is not how humans read,” said co-author David Hardman, also from the Department of Engineering. “Existing robotic braille readers work in a static way: they touch one letter pattern, read it, pull up from the surface, move over, lower onto the next letter pattern, and so on. We want something that’s more realistic and far more efficient.”

̽��ֱ��robotic sensor the researchers used has a camera in its ‘fingertip’, and reads by using a combination of the information from the camera and the sensors. “This is a hard problem for roboticists as there’s a lot of image processing that needs to be done to remove motion blur, which is time and energy-consuming,” said Potdar.

̽��ֱ��team developed machine learning algorithms so the robotic reader would be able to ‘deblur’ the images before the sensor attempted to recognise the letters. They trained the algorithm on a set of sharp images of braille with fake blur applied. After the algorithm had learned to deblur the letters, they used a computer vision model to detect and classify each character.

Once the algorithms were incorporated, the researchers tested their reader by sliding it quickly along rows of braille characters. ̽��ֱ��robotic braille reader could read at 315 words per minute at 87% accuracy, which is twice as fast and about as accurate as a human Braille reader.

“Considering that we used fake blur the train the algorithm, it was surprising how accurate it was at reading braille,” said Hardman. “We found a nice trade-off between speed and accuracy, which is also the case with human readers.”

“Braille reading speed is a great way to measure the dynamic performance of tactile sensing systems, so our findings could be applicable beyond braille, for applications like detecting surface textures or slippage in robotic manipulation,” said Potdar.

In future, the researchers are hoping to scale the technology to the size of a humanoid hand or skin. ̽��ֱ��research was supported in part by the Samsung Global Research Outreach Program.

Reference:
Parth Potdar et al. ‘High-Speed Tactile Braille Reading via Biomimetic Sliding Interactions.’ IEEE Robotics and Automation Letters (2024). DOI: 10.1109/LRA.2024.3356978

Researchers have developed a robotic sensor that incorporates artificial intelligence techniques to read braille at speeds roughly double that of most human readers.

Can robots read braille?

Parth Potdar

Robot braille reader

̽��ֱ��text in this work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. Images, including our videos, are Copyright © ̽��ֱ�� of Cambridge and licensors/contributors as identified. All rights reserved. We make our image and video content available in a number of ways – on our main website under its Terms and conditions, and on a range of channels including social media that permit your use and sharing of our content under their respective Terms.

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Self-healing materials for robotics made from ‘jelly’ and salt

sc604 — Fri, 18 Feb 2022 16:54:17 +0000

̽��ֱ��low-cost jelly-like materials, developed by researchers at the ̽��ֱ�� of Cambridge, can sense strain, temperature and humidity. And unlike earlier self-healing robots, they can also partially repair themselves at room temperature.

̽��ֱ��results are reported in the journal NPG Asia Materials.

Soft sensing technologies could transform robotics, tactile interfaces and wearable devices, among other applications. However, most soft sensing technologies aren’t durable and consume high amounts of energy.

“Incorporating soft sensors into robotics allows us to get a lot more information from them, like how strain on our muscles allows our brains to get information about the state of our bodies,” said David Hardman from Cambridge’s Department of Engineering, the paper’s first author.

As part of the EU-funded SHERO project, Hardman and his colleagues have been working to develop soft sensing, self-healing materials for robotic hands and arms. These materials can detect when they are damaged, take the necessary steps to temporarily heal themselves and then resume work – all without the need for human interaction.

“We’ve been working with self-healing materials for several years, but now we’re looking into faster and cheaper ways to make self-healing robots,” said co-author Dr Thomas George-Thuruthel, also from the Department of Engineering.

Earlier versions of the self-healing robots needed to be heated in order to heal, but the Cambridge researchers are now developing materials that can heal at room temperature, which would make them more useful for real-world applications.

“We started with a stretchy, gelatine-based material which is cheap, biodegradable and biocompatible and carried out different tests on how to incorporate sensors into the material by adding in lots of conductive components,” said Hardman.

̽��ֱ��researchers found that printing sensors containing sodium chloride – salt – instead of carbon ink resulted in a material with the properties they were looking for. Since salt is soluble in the water-filled hydrogel, it provides a uniform channel for ionic conduction – the movement of ions.

When measuring the electrical resistance of the printed materials, the researchers found that changes in strain resulted in a highly linear response, which they could use to calculate the deformations of the material. Adding salt also enabled sensing of stretches of more than three times the sensor’s original length, so that the material can be incorporated into flexible and stretchable robotic devices.

̽��ֱ��self-healing materials are cheap and easy to make, either by 3D printing or casting. They are preferable to many existing alternatives since they show long-term strength and stability without drying out, and they are made entirely from widely available, food-safe, materials.

“It’s a really good sensor considering how cheap and easy it is to make,” said George-Thuruthel. “We could make a whole robot out of gelatine and print the sensors wherever we need them.”

̽��ֱ��self-healing hydrogels bond well with a range of different materials, meaning they can easily be incorporated with other types of robotics. For example, much of the research in the Bio-Inspired Robotics Laboratory, where the researchers are based, is focused on the development of artificial hands. Although this material is a proof-of-concept, if developed further, it could be incorporated into artificial skins and custom-made wearable and biodegradable sensors.

This work was supported by the Self-HEaling soft RObotics (SHERO) project, funded under the Future and Emerging Technologies (FET) programme of the European Commission.

Reference:
David Hardman, Thomas George-Thuruthel, and Fumiya Iida. ‘Self-Healing Ionic Gelatin/Glycerol Hydrogels for Strain Sensing Applications.’ NPG Asia Materials (2022). DOI: 10.1038/s41427-022-00357-9

Researchers have developed self-healing, biodegradable, 3D-printed materials that could be used in the development of realistic artificial hands and other soft robotics applications.

It’s a really good sensor considering how cheap and easy it is to make

Thomas George-Thuruthel

Self healing robot developed by Cambridge Uni engineers

̽��ֱ��text in this work is licensed under a Creative Commons Attribution 4.0 International License. Images, including our videos, are Copyright © ̽��ֱ�� of Cambridge and licensors/contributors as identified. All rights reserved. We make our image and video content available in a number of ways – as here, on our main website under its Terms and conditions, and on a range of channels including social media that permit your use and sharing of our content under their respective Terms.

Yes