Comparison Between a Concurrent and a Sequential Optimization Methodology for Serial Manipulators Using Metaheuristics

A concurrent optimum design of a manipulator is to find the best geometrical and control parameters in the same optimization process. One of the main contributions of this paper is a concurrent method for optimum design and its comparison versus a sequential one, where the later requires several optimization stages. Besides, we statistically compare three metaheuristics: the Omnioptimizer, the covariance matrix adaptation evolutionary strategy, and the Boltzmann univariate marginal distribution algorithm for the two methodologies, in order to elucidate directions about which metaheuristic performs the best for this kind of problem, and whether it must be used in a sequential or concurrent fashion. These metaheuristics are compared with reported results in the specialized literature. In addition, we perform an analysis of results to statistically determine relations between the parameters and the objective function, as a consequence, we found the most impacting parameters to the manipulator performance.