more about evolving bodies than just brains, but both are interesting. Areas such as simulated physics, modelling of machines, building from design, etc are all appropriate, moreso the real world errors that creep in.
A multidisciplinary research group at the University of Calabria (Italy) is working on evolutionary robotics in which neural network and genetic algorithms are applied to select the fittest behaviour. Robots may change during lifetime and adapt to their (varying) environment. Collaboration with industrial research centres and universities is sought for a joint development into specific application fields.
Evolutionary Robotics is a technique for the automatic creation of autonomous robots that is inspired by the Darwinian principle of selective reproduction of the fittest. The basic idea behind evolutionary robotics is the following:
The technique is based on the selection of neural networks by means of genetic algorithms, on the basis of their competence to achieve a given objective. A behaviour can be first selected in a software simulated environment and then the “emerging” behaviour can be applied to a physical robot and tested on a real ground.
Robots might also change during lifetime and therefore might adapt to their environment. Artificial evolution might lead to the development of simple and effective solutions also in the case of problems that have to be solved in varying environmental conditions.
Main Advantages:
Innovative Aspects: It is a new approach that looks at robots as autonomous artificial organisms that develop their own skills in close interaction with the environment without human intervention.
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