PhD Document - Universidad de Las Palmas de Gran Canaria

CHAPTER 3. APPROACH AND ARCHITECTURE
• We are obtaining knowledge of exactly that what we want to reproduce, which in a
sense provides some guarantee that the effort is worthwhile. That knowledge is, to say
the least, a good starting point.
• The study of human intelligence and capacities has produced and is still producing
invaluable results. Advances in neuroscience have been particularly significant in the
last fifteen years, in part thanks to the aid of new exploratory techniques like magnetic
resonance imaging.
By contrast, the synthetic approach aims at building artificial systems, see Figure 3.1.
The goal is not so much to know how the object is, but how it should be to fulfil a series of
requirements. This can be done to pursue three goals [Pfeifer and Scheier, 1999]:
• To model biological systems
• To explore principles of intelligence
• To develop applications
As Figure 3.1 shows, analysis and synthesis complement one another. Every synthe-
sis is built upon the results of a preceding analysis, and every analysis requires a subsequent
synthesis in order to verify and correct its results.
Analysis
Other sources of
knowledge or inspiration
Synthesis
human robot
Figure 3.1: Analysis and Synthesis.
In Chapter 1 it was observed that for social robots there may be less guarantee of good
performance than in other types of robots. The fact is that, for some types of machines like
robotic manipulators, one can extract a set of equations (or algorithms, representations,...)
that are known to be valid for solving the task. Such equations would have been obtained
after analytical effort, mainly related to kinematics. Once that these equations are stored in
the control computer the manipulator will always move to desired points and therefore there
is a sort of deductive process involved.
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