A Neural Network force control of a robot manipulator collaborating with a human to handle a fabric is presented. A robotic gripper holds the one end of a piece of fabric while a human hand holds the opposite end. As the human moves the fabric arbitrarily, the robot tries to manipulate the fabric according to the required handling task. The task could be defined in a higher-level decision making process which is based on the artificial constrains of the handling task and influenced by the human needs. A force sensor mounted on the wrist of the robot manipulator measures the 3-components (F{sub}x, F{sub}y, F{sub}z) of the actual force applied by the human hand to the fabric, and the formulated force errors are used in the backpropagation algorithm, which trains the Neural Network force controller. The controller is tested in a simple case of a desired handling task and the results are discussed and compared with the reversed case, i.e. the robot moves the fabric arbitrarily and the human tries to manipulate the fabric according to the handling task. The response of the controller show that the robot is capable to handle the fabric according to the desired constrains.
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