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CNN has a great potential for signal processing tasks
and it can generate very
complex nonlinear waves and oscillation patterns at the output of CNN cells.
Controlling both the kinematic and the inverse-kinematic of complex robots with
high degree of freedom (DOF) is a very complex
scenario whereby classical
solutions fail to solve it easily. In the frame of this research question we have
integrated a CNN processors system to the leg-robot
for high level inverse
kinematic controlling. For calculating templates we used GA and a very simple
objective function without considering any inverse or direct kinematic. Different
types of robots are able to move in an optimum way
between two points or any
kind of other scenarios and trajectories.
As outlook and future work we do see the integration of all functionalities developed in
this thesis in a working prototype and improve it progressively according to test results in
the real environment.
