Determination of rotation angle based on invariant moment and MADALINE for HGA grasping

Abstract

To proposed a new adaptive intelligent system for a robot work cell that can visually track and intercept an invariant stationary HGA feature undergoing arbitrary orientation anywhere along its predicted trajectory within the robot’s workspace is presented in this paper. A combination of the seven invariant moment technique, image feature technique and the MADALINE network are used for identifying the stationary HGA at any rotation angle without overlapping and generating the predicted robot trajectory respectively. An invariant moment that has system for a scale, translation and orientation are calculated for each significant region in the input images. Inertial ellipse is determining for angle rotation that compare against to the accepted orientation that required. The result shown that, the relationship between the visual feedback image data and the control command for changing the axis motion shows deviation of robot placing less than 2% by the MADALINE network for intercepting stationary HGA at any rotation angle. The location and image features of these HGAs need not be preprogrammed, marked and known before, and any change in a task is possible without changing the robot program. Finally, this novel method can improve the hard disk drive (HDD) assembly process productivity.

Keywords

• HGA
• Invariant moment
• Orientation angle
• MADALINE