Please use this identifier to cite or link to this item:
|Title:||Control of Robotic Fixtureless Assembly|
|Authors:||Yuen, Ming Ka|
Elbestawi, M. A.
|Keywords:||Mechanical Engineering;Mechanical Engineering|
|Abstract:||<p>Robotic Fixtureless Assembly (RFA) refers to the performance of assembly tasks by robots without the aid of jigs and fixtures. Two control problems encountered in RFA of sheet metal parts assembly are addressed in this thesis. They are the control of vibration when handling the sheet metal parts and the control of the contact state between the parts during assembly. Both 2-D parts and 3-D parts will be considered when the two problems are addressed. A unique sensor, termed a Strain Gauge equipped Finger (SGF), was first developed which can measure the part's vibration during handling and the contact state during assembly. For the vibration control problem, a novel Learning Extremum Control (LEC) algorithm is proposed. Using SGF's mounted on the robot gripper for vibration feedback, the orientation of the part in 3-D space relative to its path is controlled to reduce vibration. Furthermore, as an alternate approach, a feedforward Input Command Shaping Method (ICSM) is employed to reduce the vibration. Experimental results confirmed the effectiveness of both control algorithms. The LEC and the ICSM reduced the vibration amplitude by up to 71% and 78%, respectively. In order to solve the contact state control problem, the contact state measurement problem in 2-D parts assembly is first considered. Measurement methods are developed based on the use of a Force/Moment Sensor (FMS) alone, SGFs alone and the sensor fusion of he FMS and SGFs information. The methods are verified in 160 robotic assembly trials. The success rate for the FMS method increased from 28% to 88% when the sheet thickness was increased from 0.32 mm to 1.88 mm. Under the same conditions, the success rate for the SGF method decreased from 100% to 55%. The sensor fusion method surpassed the best individual performances off the other methods by achieving a 100% success rate for the complete set of sheet thicknesses and contact states tested. After the contact state measurement problem is considered, the contact state control problem is examined. The SGFs a Force/Moment Sensor (FMS) are used to provide feedback about the contact condition between two sheet metal parts. An Integral Contact Controller (ICC) is used to correct angular error between the parts to ensure full contact along the joints for subsequent welding. Experimental results confirmed the effectiveness of the ICC algorithms. For 2-D parts, using the fusion of the FMS and SGF sensory information, the ICC reduced the Yaw joint angular error from 0.5˚ to 0.025˚ within 1.7 seconds. For 3-D parts, the ICC reduced the angular error in both the Pitch and Yaw angles from 0.5˚ to 0.05˚ within 2.4 and 3.6 seconds using the FMS alone and SGFs alone, respectively. Finally, an investigation is performed to determine the effectiveness of applying the Input Command Shaping Method in the contact state control experiments. This method's limitations are discussed.</p>|
|Appears in Collections:||Open Access Dissertations and Theses|
Items in MacSphere are protected by copyright, with all rights reserved, unless otherwise indicated.