Researchers at DLR took the same approach. The artificial arm they built and are now experimenting with uses a total of 58 motors in opposing pairs, coupled with non-linear springs, to control the arm.
The hand they have built is closely modelled on the human hand. It can snap its fingers, pick up an egg or carry a cup of coffee. Its fingers are moved by 38 opposing motors.
Again, the researchers had to go back to basics, for example making detailed MRI studies of human hands in hundreds of different positions. "Surprisingly enough, this doesn't exist anywhere else," says van der Smagt.
How to build a brain
From the start, the group knew that sensitivity, dexterity, and strength were not enough. They had to provide the biomimetic arm with a high degree of intelligence.
Their ultimate goal is to create a microchip that will allow the arm to carry out tasks requiring human-level skills in a real-world setting.
Van der Smagt envisions an arm that could "decide" to pick up a cup, sense important properties of what it contains, for example water versus flour, and move it from place to place.
"It's not that the system needs to know that there's water in the cup," says van der Smagt, "but how to handle whatever is in it appropriately."
Scientists at the University of Edinburgh, in Scotland, and at Lund University, in Sweden, decided that the best approach was to model the human cerebellum. The cerebellum is a fist-sized organ at the base of the brain that coordinates sensation and movement.
The researchers are currently using software to simulate important aspects of how the cerebellum processes and integrates information. "It's the first neural-network-based controller that can control the dynamics of a robotic system in its fu
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