Physical Sciences and Mathematics Commons^™

Robotic System Sensitivity To Neural Network Learning Rate: Theory, Simulation, And Experiments, Christopher M. Clark, James K. Mills

Computer Science and Software Engineering

Selection of neural network learning rates to obtain satisfactory performance from neural network controllers is a challenging problem. To assist in the selection of learning rates, this paper investigates robotic system sensitivity to neural network (NN) learning rate. The work reported here consists of experimental and simulation results. A neural network controller module, developed for the purpose of experimental evaluation of neural network controller performance of a CRS Robotics Corporation A460 robot, allows testing of NN controllers using real-time iterative learning. The A460 is equipped with a joint position proportional, integral, and derivative (PID) controller. The neural network module supplies …