A virtual end-effector pointing system in point-and-direct robotics for inspection of surface flaws using a neural network based skeleton transform

The development of a system for interweaving virtual reality tools with live video scenes to direct robots using video graphic gestures is described. This virtual point-and-direct (V-PAD) concept is applied to workpiece inspection. a normalized coding method is employed for surface flaw identification using a neural network based skeleton transform. The method is scale, location, and orientation invariant so that robotic placement of workpieces for inspection requires no exact precision from special fixturing