Hand control by a neural network using tactile and positional information

The development of manipulators with perceptive tactile capabilities which are really similar to those of the human hand has been hindered until now by the complexity of the sensory structures involved. Furthermore, sensors and actuators need to be closely integrated. The paper considers contact touch, a particular perceptive capability, during tasks that don´t require force; and studies how it can be used by the actuators to control the movements of the hand. The organization that the authors propose is implemented with a structured neural network. Backpropagation is used to map tactile receptors onto motor actuators.<>