February 4, 2014
Robot Uses Insect Brain To Navigate Arena
[ Watch the Video: Robotic Honey Bee Brains ]
Lee Rannals for redOrbit.com - Your Universe Online
Scientists using the nervous system of the honeybee as a model have developed a robot that perceives environmental stimuli and learns to react to them. This robot was able to replicate the sensorimotor network of the insect brain, bringing with it a new dawn of robotic insects.
The researchers, from Freie Universität Berlin and Bernstein Center Berlin, installed a camera on a small robotic vehicle and connected it to a computer, which acted as the insect brain. The data from the camera worked as an eye, while the neural network operated the motors of the robot, enabling it to control its motion direction.
"The network-controlled robot is able to link certain external stimuli with behavioral rules," Prof Martin Paul Nawrot, head of the research team and professor of neuroscience at Freie Universität Berlin, said in a statement. "Much like honeybees learn to associate certain flower colors with tasty nectar, the robot learns to approach certain colored objects and to avoid others."
The scientists placed their robotic insect in the center of a small arena plastered with red and blue objects on the walls. When the robot’s camera focused on an object with the desired color, the scientists triggered a light flash that activated a reward sensor nerve cell in the artificial network. Associating the color with a reward led to specific changes in those parts of the network, meaning that if the robot insect saw another object of the same color again it would start to move towards it.
When the reward center kicked in, the red objects on the walls would make the robot move forward, while the blue items made it move backwards.
"Just within seconds, the robot accomplishes the task to find an object in the desired color and to approach it," said Nawrot. "Only a single learning trial is needed, similar to experimental observations in honeybees."
Next, the scientists are planning to expand the neural network by supplementing more learning principles. This study would enable the robot brain to become even more powerful, allowing it to move more autonomously and expand its knowledge.