A genetic algorithm to optimum dynamic performance of industrial robots in the conceptual design phase

One of the most important criteria of the industrial robots is the dynamic performance of manipulators. There are some critical parameters which determine the dynamic performance of robot manipulators. While the correlations between these parameters are complex and highly non-linear, deciding on these parameters to optimize the dynamic performance of manipulators is a difficult and time-consuming task, especially in the early conceptual design phase. The gearbox size and the lengths of the arms are parameters that have a large impact on the performance and the cost of robots. In order to perform optimization, a mathematical programming model is developed. An objective function is defined to determine optimal gearboxes and arm lengths from an acceleration capability perspective. The arm lengths are treated as continuous variables whereas the gearboxes are selected from a list of available units. This paper presents a Genetic algorithm procedure which shows how optimization can be used in the early phases of a development process in order to evaluate the potential of a concept. This study considers a three degree of freedom robot. The mathematical model is coded in the C language and optimized using the Genetic algorithm. Comparison of the obtained results with optimum values based on Complex algorithm, clearly shows the advantages of the proposed method.