Improving the dexterity of robot hands could have significant implications for automating tasks such as handling goods for supermarkets or sorting through waste for recycling.

Led by Professor of Robotics and AI Professor Nathan Lepora, the team at the University of Bristol have created a four-fingered robotic hand with artificial tactile fingertips capable of rotating objects such as balls and toys in any direction and orientation. It can even do this when the hand is upside down – something which has never been done before.

In 2019, OpenAI became the first to show human-like feats of dexterity with a robot hand. However, despite making front-page news, OpenAI soon disbanded their 20-strong robotics team. OpenAI’s set up used a cage holding 19 cameras and more than 6,000 CPUs to learn huge neural networks which could control the hands, but this operation would have required significant costs.

Professor Lepora and his colleagues wanted to see if similar results could be achieved using simpler and more cost-efficient methods. In the past year, four university teams from MIT, Berkeley, New York (Columbia) and Bristol have shown complex feats of robot hand dexterity from picking up and passing rods to rotating children’s toys in-hand – and all have done so using simple set-ups and desktop computers.

As detailed in the recent Science Robotics article “The future lies in a pair of tactile hands”, the key advance that made this possible was that the teams all built a sense of touch into their robot hands. Developing a high-resolution tactile sensor became possible thanks to advances in smartphone cameras which are now so tiny they can comfortably fit inside a robot fingertip.

Read the full University of Bristol news item

'The future lies in a pair of tactile hands' by Nathan F. Lepora in Science Robotics

'AnyRotate: Gravity-invariant in-hand object rotation with sim-to-real touch' by M Yang, C Lu, A Church, Y Lin, C Ford, H Li, E Psomopoulou, D Barton, N Lepora in Robotics