Abstract:
This work aims at developing a motor path
generator for applications in mobile robotics based on a
chaotic neural network. The computational paradigm inspired
by the neural structure of microcircuits located in the human
prefrontal cortex is adapted to work in real-time and used
to generate the joints trajectories of a lightweight quadruped
robot. The recurrent neural network was implemented in
Matlab and a software framework was developed to test the
performances of the system with the robot dynamic model.
Preliminary results demonstrate the capability of the neural
controller to learn period signals in a short period of time
allowing adaptation during the robot operation