Visually Guided Coordination for Distributed Precision Assembly

This report documents the integration of machine vision into the minifactory environment. Minifactory is an automated factory system being developed at the Microdynamic Systems Laboratory at Carnegie Mellon University and is aimed toward the assembly of small mechatronic devices. Machine vision can aid assembly systems by eliminating the need for complicated part holding jigs, end effectors, and part feeding equipment. In addition, the position accuracy of a visually servoed robot can be made relatively insensitive to robot calibration errors. By using the visual control and communications systems described in this report, two high-precision 2-DOF robotic agents were visually guided to precisely align parts of a sub-assembly. Test results show that open-loop look-and-move alignment of parts took an average of 3.7 iterations and 3.6 seconds while visual servoing alignment took an average of 1.3 seconds. The standard deviation of the visual servoing alignment errors for the u and v axes were 4.6 m and 5 m respectively. However, they were limited by tracker noise which was approximately 10 m peak to peak with a standard deviation of 2 m in the u axis of the image plane and 20 m peak to peak with a standard deviation of 6 m in the v axis. Overall, the vision project’s greatest success was making two 2-DOF agents transiently cooperate to function as a single 4-DOF robot to perform visual servoing tasks. Thesis supervisor: Dr. Ralph Hollis Principal Research Scientist, Robotics Institute First reader: Dr. Robert M. White Professor of Electrical and Computer Engineering and Engineering and Public Policy Director of the Data Storage Systems Center Second reader: Dr. Gary K. Fedder Associate Professor of Electrical and Computer Engineering and the Robotics Institute