In this paper, 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. These approaches were used for the optimum design of SCARA and articulated type manipulators. The objective function minimizes the torque required for the motion subject to deflection and physical constraints with the design variables being the physical characteristics of link (length and cross sectional area parameters). In this work, we experimented links with various cross sections. The main findings of this research are that the differential evolution converges quickly, requires significantly less number of iterations and achieves better results.

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