A software-based procedure for robotic end effector error correction

Presents a procedure for modeling and eliminating an end effector configuration error as a result of a faulty joint or a damaged link. This procedure provides an inexpensive software alternative to hardware replacement. A neural network model was developed and tested an a 6 DOF PUMA robot. The network approximates the error based on data obtained through observing the robot while executing a set of MOVE commands. The results show that, regardless of the error source, the robot´s accuracy could be highly improved even when a small number of data points are used