Neural network force control for robotized handling of fabrics

Abstract

A neural network force controller for regulating the fabric's tensional forces applied by a robot in fabric handling tasks is presented. The proposed controller enables the robot to apply a desired constant force to the fabric in a dynamically changing environment (fabric's variable and unknown velocity and length). A force sensor mounted on the wrist of the robot manipulator measures the actual force applied to the fabric, and the formulated force error is used in the backpropagation algorithm which trains the controller. Two real fabric handling examples are presented for testing the effectiveness of the controller, where the robot demonstrates a satisfactory real-time response. The feedforward neural network (FNN) controller is tested and the results are discussed and compared to those obtained using a PID controller under the same conditions. The performance of both controllers is investigated and a computational comparison is carried out.