Vision-based Object Tracking Experiment for Students to Perform Simple Industrial Robotic Automation

Abstract

He received his Ph.D. degree in the G.W. Woodruff School of Mechanical Engineering at Georgia Institute of Technology. His educational background is in manufacturing with an emphasis on mechatronics. In addition to his many years of industrial experience, he has taught many different engineering and technology courses at undergraduate and graduate levels. His tremendous research experience in manufacturing includes environmentally conscious manufacturing, Internet based robotics, and Web based quality. In the past years, he has been involved in sustainable manufacturing for maximizing energy and material recovery while minimizing environmental impact.

Manipulator Trajectory Tracking Based on Kinematics Model Predictive Control

“…After improving the Denavit-Hartenberg (DH) parameters, Ragaglia et al [13] constructed a homogeneous transformation matrix between the rods of the industrial robot, built a kinematics model of the robot system through Newton-Euler iterative method, and calculated the working efficiency and error of the robot on MATLAB. Chiou and Sowmithran [14] transformed trajectory optimization into finite-dimensional secondorder cone programming, and obtained the numerical solution to the time-optimal trajectory; afterwards, Pan et al [15] introduced the velocity-related torque constraints, and added the limitation of system energy consumption and total acceleration of motion, thereby effectively reducing the trajectory optimization time and energy consumption. Pan et al [15] fitted the expected curve for the ideal robot trajectory by the segmented trajectory planning algorithm, and calculated the length of the curve with the compound Cotes formula.…”