Scientists from the University of Cambridge have developed a 3D-printed robotic hand that can play simple musical notes on a piano by just moving its wrist.

The hand was made by 3D-printing soft and rigid materials together to replicate the bones and ligaments but not the muscles or tendons of a human hand. The robotic hand isn’t perfect as evidenced in the video where it makes mistakes playing the holiday song “Jingle Bells,” but it is more of an experiment to show how complex movement in robotics can be achieved through design, the university said.

While the hand has limited range of motion compared to a human hand, researchers found that a wide range of movement was still possible by relying on the mechanical design, which uses passive movement where the fingers cannot move independently. However, the robotic hand was still able to mimic different styles of piano playing without changing the material or mechanical properties.

"We can use passivity to achieve a wide range of movement in robots: walking, swimming or flying, for example," said Josie Hughes from Cambridge's Department of Engineering. "Smart mechanical design enables us to achieve the maximum range of movement with minimal control costs: we wanted to see just how much movement we could get with mechanics alone."

Researchers said playing piano is a good test for passive systems because it is a complex and nuanced challenge requiring a range of behaviors to achieve different playing styles.

"Our bodies consist of smart mechanical designs such as bones, ligaments, and skins that help us behave intelligently even without active brain-led control,” said Fumiya Iida, a professor at Cambridge who led the research. “By using the state-of-the-art 3D printing technology to print human-like soft hands, we are now able to explore the importance of physical designs, in isolation from active control, which is impossible to do with human piano players as the brain cannot be 'switched off' like our robot."

Teaching It to Play

Researchers “taught” the robotic hand by considering how the mechanics, material properties, environment and wrist actuation all affect the dynamic model of the hand. By actuating the wrist, it was possible to choose how the hand interacts with the piano, allowing the hand to determine how it interacts with the musical instrument.

They then programmed the robot to play a number of short musical phrases with clipped or smooth notes.

Researchers believe the approach will help to drive further research into the underlying principles of skeletal dynamics to achieve complex movement tasks as well as to learn where the limitations for passive movement systems reside. This research also will help to change how companies fabricate robotics.

"We can extend this research to investigate how we can achieve even more complex manipulation tasks: developing robots which can perform medical procedures or handle fragile objects, for instance," Hughes said. "This approach also reduces the amount of machine learning required to control the hand; by developing mechanical systems with intelligence built in, it makes control much easier for robots to learn."

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