Neural network approach to firm grip in the presence of small slips
The authors deal with a two-stage method to examine a firm grip that can tolerate small slips of finger tips of frictionless contact type. The interaction in the gripper-object system is used as a static mapping in training of a neural network. Genetic algorithms have been used in training another neural network by applying global optimization techniques. Hence, the resulting neural network becomes a robust, reliable and stable controller for rigid bodies handled by a robot gripper.
scientific article; zbMATH DE number 1625341