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Two control problems encountered in robotic sheet metal assembly are addressed in this paper. They are the control of vibration when handling the sheet metal parts and the control of the contact state between the parts during assembly. For the first problem, a Learning Extremum Controller (LEC) is proposed. Using a strain gauge based sensing device mounted on the robot gripper for vibration feedback, the orientation of the part relative to its path is controlled to reduce vibration. For the second problem, a sensor fusion system developed previously [lo] is used to provide feedback about the contact condition between two sheet metal parts. An Integral Contact Controller (ICC) is used to correct any angular error between the parts to ensure full contact along the joint for subsequent welding. Experimental results confirmed the effectiveness of both control algorithms. The LEC reduced the vibration amplitude by up to 45%. The ICC reduced the angular error from 0.5" to 0.025" in 1.7 seconds.

A lack of fixturing flexibility and of high speed handling of non-rigid parts are two important problems in automotive sheet metal assembly operations. This paper describes the development of two unique grippers for flexible fixturing of automotive sheet metal parts, and of two methods for the vibration control needed for high speed handling of non-rigid parts. Each gripper is designed to execute a 3-D fixturing strategy which does not require accurate initial part placement, and provides a large number of valid fixturing solutions. Both grippers are tested on several automotive parts. With the first design, the average standard deviation of the parts’ location before fixturing of 0.5 mm was reduced to 0.01 mm after fixturing. The methods of vibration control may be used with most of the industrial robots used for part handling. At a speed of 1 m/s the LEC method reduced the vibration amplitude by 33% after four learning trials. At 0.5 m/s the ICS method reduced the vibration amplitude by 60% and the settling time by 67%.