Robot control using high dimensional neural networks

In this paper, we propose a position control scheme for actual robot system using high dimensional neural networks. Complex-valued neural network and quaternion neural network learn inverse kinematics of the robot systems. Control objectives are two dimensional SCARA robot and three dimensional robot. Tip of these robots are controlled by the high dimensional neural networks. Some results by an actual robot system are shown to confirm feasibility of these high dimensional neural networks as robot controllers.