Research on the Form Recognition of Fabric Products: Acquiring the Shapes of Flat, Limp Materials

In the apparel, medical and welfare, and nursing care industries, working with cloth items is highly dependent on manual work, so many people have hoped that such work could be automated. However, there are still no established ways for robots to handle cloth. In this paper, a method for acquiring developed shapes is proposed for the purpose of form recognition and classification operations of flat, limp materials. Experiments are performed to acquire developed shapes of materials by actively searching for contours of cloth using a sensor embedded in the finger of a robot.

MODELING AND DYNAMIC ANALYSIS OF RECONFIGURABLE ROBOTIC GRIPPER SYSTEM FOR HANDLING FABRIC MATERIALS IN GARMENT INDUSTRIES

A reconfigurable robotic gripper based on pneumatic technology has been designed and developed for grasping fabric materials in garment industries automation. The design is based on reconfigurable multidegree of freedom, which can manipulate single and multiple panels of limp materials. The design consist of four arms initially in a cross bar configuration, hosting four suction cups mounted on each of the arms. The design assures low inertia, high modularity and full flexibility adapting to the picking of limp materials in garment and shoe industries. The simulation referring to a worst-case operative cycle has been performed in the environment of a current industrial layout. The kinematic and dynamic performance of the gripper system is analyzed in ADAMS simulation software and the results are presented. The architecture of the gripper is simple and the choice of pneumatic actuators improves the reliability of the system.