The introduction of microassembly technologies has opened up new venues for the fabrication of sophisticated, three-dimensional Microelectromechanical System (MEMS) devices. This thesis presents the development of a robotic micromanipulation system and its controller algorithms for conventional pick-and-place microassembly processes. This work incorporated the approach of parallel assembly and automation to improve overall productivity and reduce operating costs of the process. A parallel set of three microgrippers was designed and implemented for the grasping and assembly of three microparts simultaneously. The complete microassembly process was automated through a vision-based control approach. Visual images from two vision systems were adopted for precise position evaluation and alignment. Precise alignment between the micropart and microgripper is critical to the microassembly process. Due to the limited field of view of the vision systems, the micropart could displace away from the microscope field of view during the re-orientation process. In this work, a tracking algorithm was developed to constrain the micropart within the camera view. The unwanted translational motions of the micropart were estimated. The algorithm then continuously manipulated and repositioned the micropart for the vision-based assembly. In addition, the limited fields of view of the vision systems are not sufficient to concurrently monitor the assembly operation for all three individual grippers. This work presents a strategy to use visual information from only one gripper set for all the necessary alignment and positioning processes. Through proper system calibration and the alignment algorithms developed, grippers that were not visually monitored could also perform the assembly operations. When using visual images from a single vision camera for 3D positioning, the extra dimension between the 2D image and 3D workspace results in errors in position evaluation. Hence, a novel approach is presented to utilize image reflection of the micropart for online evaluation of the Jacobian matrix. The relative 3D position between the slot and micropart was evaluated with high precision. The developed algorithms were integrated onto the micromanipulation system. Automated parallel microassemblies were conducted successfully.

The introduction of microassembly technologies has opened up new venues for the fabrication of sophisticated, three-dimensional Microelectromechanical System (MEMS) devices. This thesis presents the development of a robotic micromanipulation system and its controller algorithms for conventional pick-and-place microassembly processes. This work incorporated the approach of parallel assembly and automation to improve overall productivity and reduce operating costs of the process. A parallel set of three microgrippers was designed and implemented for the grasping and assembly of three microparts simultaneously. The complete microassembly process was automated through a vision-based control approach. Visual images from two vision systems were adopted for precise position evaluation and alignment. Precise alignment between the micropart and microgripper is critical to the microassembly process. Due to the limited field of view of the vision systems, the micropart could displace away from the microscope field of view during the re-orientation process. In this work, a tracking algorithm was developed to constrain the micropart within the camera view. The unwanted translational motions of the micropart were estimated. The algorithm then continuously manipulated and repositioned the micropart for the vision-based assembly. In addition, the limited fields of view of the vision systems are not sufficient to concurrently monitor the assembly operation for all three individual grippers. This work presents a strategy to use visual information from only one gripper set for all the necessary alignment and positioning processes. Through proper system calibration and the alignment algorithms developed, grippers that were not visually monitored could also perform the assembly operations. When using visual images from a single vision camera for 3D positioning, the extra dimension between the 2D image and 3D workspace results in errors in position evaluation. Hence, a novel approach is presented to utilize image reflection of the micropart for online evaluation of the Jacobian matrix. The relative 3D position between the slot and micropart was evaluated with high precision. The developed algorithms were integrated onto the micromanipulation system. Automated parallel microassemblies were conducted successfully.