Researchers of Freie Universität
Berlin, of the Bernstein Fokus Neuronal Basis of Learning, and of the Bernstein
Center Berlin and have developed a robot that perceives environmental stimuli
and learns to react to them. The scientists used the relatively simple nervous
system of the honeybee as a model for its working principles. To this end, they
installed a camera on a small robotic vehicle and connected it to a computer.
The computer program replicated in a simplified way the sensorimotor network of
the insect brain. The input data came from the camera that-akin to an
eye-received and projected visual information. The neural network, in turn,
operated the motors of the robot wheels-and could thus control its motion
direction. The outstanding feature of this artificial mini brain is its ability
to learn by simple principles.
In the learning experiment, the
scientists located the network-controlled robot in the center of a small arena.
Red and blue objects were installed on the walls. Once the robot's camera
focused on an object with the desired color (i.e. red), the scientists
triggered a light flash. This signal activated a so-called reward sensor nerve
cell in the artificial network. The simultaneous processing of red color and
the reward now led to specific changes in those parts of the network, which
exercised control over the robot wheels. As a consequence, when the robot
"saw" another red object, it started to move toward it. Blue items,
in contrast, made it move backwards. The scientists are now planning to expand
their neural network by supplementing more learning principles. Thus, the mini
brain will become even more powerful-and the robot more autonomous.
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