Forum for Science, Industry and Business

Sponsored by:     3M 
Search our Site:

 

Robots with insect brains

03.02.2014
Berlin researchers develop a robot that can learn to navigate through its environment guided by external stimuli. It operating principles? The brain of insects.

The robot in the arena. The small camera films the objects and passes the information to the neural network by wifi. The network processes the data and controls the movement direction of the robot.

Martin Paul Nawrot

Autonomous robots that find their way through unfamiliar terrain? Not so distant future.

Researchers at the Bernstein Fokus Neuronal Basis of Learning, the Bernstein Center Berlin and the Freie Universität Berlin 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 artifical mini brain is its ability to learn by simple principles. “The network-controlled robot is able to link certain external stimuli with behavioral rules,” says Professor Martin Paul Nawrot, head of the research team and member of the sub-project „Insect inspired robots: towards an understanding of memory in decision making“ of the Bernstein Focus. “Much like honeybees learn to associate certain flower colors with tasty nectar, the robot learns to approach certain colored objects and to avoid others.”

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—red, for instance—, 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 to move backwards. “Just within seconds, the robot accomplishes the task to find an object in the desired color and to approach it,” explains Nawrot. “Only a single learning trial is needed, similar to experimental observations in honeybees.”

The current study has been carried out within an interdisciplinary collaboration between Professor Martin Paul Nawot’s research group “Neuroinformatics” (Institut of Biology), and the group “Intelligent Systems and Robotics” (Institute of Computer Science) headed by Raúl Rojas at Freie Universität Berlin. 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.

The Bernstein Focus Neuronal Basis of Learning, sub-project “Insect inspired robots: towards an understanding of memory in decision making” and the Bernstein Center Berlin are part of the National Bernstein Network Computational Neuroscience in Germany. With this funding initiative, the German Federal Ministry of Education and Research (BMBF) has supported the new discipline of Computational Neuroscience since 2004 with more than 170 million Euros. The network is named after the German physiologist Julius Bernstein (1835–1917).

Contact:
Prof. Dr. Martin Paul Nawrot
Freie Universität Berlin
Institute of Biology – Neurobiology
Königin-Luise-Straße 1-3, room 201
14195 Berlin 

Tel: +49 (0)30 838 56692
Email: martin.nawrot@fu-berlin.de
Original publication:
L. I. Helgadóttir, J. Haenicke, T. Landgraf, R. Rojas & M. P. Nawrot (2013): Conditioned behavior in a robot controlled by a spiking neural network. 6th International IEEE/EMBS Conference on Neural Engineering (NER), 891 - 894

http://dx.doi.org/10.1109/NER.2013.6696078

Video:
http://www.youtube.com/watch?v=Qb_R_E4DPYs&feature=youtu.be
Weitere Informationen:
http://www.biologie.fu-berlin.de/neuroinformatik/ Research group „Neuroinformatics“ headed by Martin Paul Nawrot
http://www.inf.fu-berlin.de/inst/ag-ki/rojas_home/pmwiki/pmwiki.php Research group „Intelligent Systems and Robotics“ headed by Raúl Rojas
https://www.bccn-berlin.de Bernstein Center Berlin
http://www.fu-berlin.de Freie Universität Berlin
http://www.nncn.de National Bernstein Network Computational Neuroscience

Mareike Kardinal | idw
Further information:
http://www.nncn.de

More articles from Information Technology:

nachricht ‘Honeybee’ robots replicate swarm behaviour
18.09.2014 | University of Lincoln

nachricht Apps for Electric Cars
18.09.2014 | Siemens AG

All articles from Information Technology >>>

The most recent press releases about innovation >>>

Anzeige

Anzeige

Event News

"Start-ups and spin-offs funding – Public and private policies", 14th October 2014

12.09.2014 | Event News

BALTIC 2014: Baltic Sea Geologists meet in Warnemünde

03.09.2014 | Event News

IT security in the digital society

27.08.2014 | Event News

 
Latest News

KTH enters the petaflop era with new supercomputer

18.09.2014 | Physics and Astronomy

Researchers convert carbon dioxide into a valuable resource

18.09.2014 | Process Engineering

How do neutron bells toll on the skin of the atomic nucleus?

18.09.2014 | Physics and Astronomy

VideoLinks
B2B-VideoLinks
More VideoLinks >>>