Experimental validation of a robust control strategy for the robot RABBIT

Abstract

In this paper, we propose an experimental validation of a new control strategy based on the use of intuitive control and neural networks CMAC in order to control the under-actuated robot RABBIT. The training of the neural networks is carried out during the simulation. When the training is finished, these neural networks are used to control the real robot. We also present an evaluation of the robustness of this control strategy.