Optimum Robot Design Based on Task Specifications Using Evolutionary Techniques and Kinematic, Dynamic, and Structural Constraints

Abstract

In this article, we discuss optimum robot design based on task specifications using evolutionary optimization approaches. The three evolutionary optimization approaches employed are Simple Genetic Algorithms, Genetic Algorithms with elitism, and Differential Evolution (DE). These approaches were used for the optimum design of SCARA and articulated type manipulators based on kinematic, dynamic and structural analyses. The objective function minimizes the torque required for the motion subject to deflection and physical constraints with the design variables being the link physical characteristics (length and cross-sectional area parameters). In this work, we experimented with various cross-sections for the links. The main findings of this research are that the DE converges quickly, requires significantly less number of iterations and achieves better results by reaching smaller objective functions.