Neural network control of intelligent end-effector for a rehabilitation robot

This paper will describe the development of a technique using an Artificial Neural Network system for the intelligent control of a rehabilitation robot that can grasp objects dexterously with active optical proximity sensors. Multi-layer neural networks are presented to process the sensor information for grasping objects dexterously via iterative learning of the network. Complex nonlinear operations for processing the information can be performed easily by the Artificial Neural Network and total processing can be performed in real-time by using a DSP system.