Design Optimization of a Robot Manipulator Using TLBO and ETLBO Algorithms

Abstract

The effectiveness of the TLBO and ETLBO algorithms is verified for design optimization of a robot manipulator by considering four cases and imposing different conditions to demonstrate the efficiency of the design process. The workspace volume is considered as an objective function. The results of the TLBO and ETLBO algorithms are compared with the SQP, GA, DE, and PSO algorithms. The computational results show that for all the four cases the TLBO and ETLBO algorithms have obtained more accurate solutions than those obtained by the other optimization methods. Design Optimization of Robot ManipulatorOver the past few decades, the interest of researchers is growing in the field of design optimization of robotic system in order to improve the system performance using advanced optimization techniques. In the present work, design optimization of a robot manipulator is considered. An industrial robot is a programmable, multifunctional manipulator designed to move materials, parts, tools, or special devices through variable programmed motions for a variety of tasks. Robots come in variety of sizes, shapes, and capabilities. Robots have four basic components namely a manipulator, an end effect which is a part of manipulator, computer controller, and a power supply. Robot anatomy is concerned with the physical construction of body, arm, and wrist of the machine. Relative movements between various components of the body, arm, and wrist are provided by a series of either sliding or rotating joints. The body, arm, and wrist assembly is called as manipulator. The manipulator is a mechanism consisting of the major linkages, minor linkages, and the end effector (gripper or tool). Robot is designed to reach a work piece within its work volume. Work volume is the term that refers to the space within which the robot can manipulate its wrist end. It is also called as work space. The surface of work space is termed as work envelop.