In this paper, an optimization design of a 6 DOF parallel measuring system is analyzed. First, a closed form direct kinematics formulation based on Cayley–Menger determinants is considered in the objective function, in order to measure the manipulator singularities, then an estimation of distribution algorithm is proposed to solve the optimization problem. It is shown that the evolutionary algorithm can find close to optimal solutions for minimum pose error estimation. Additionally, these global optimizers significantly reduce the computational burden in comparison with exhaustive search and other global optimization techniques. The sensitivity of the pose error estimation in the prescribed robots' workspace is analyzed and used to guide a designer in choosing the best structural configuration. Numerical examples are discussed to show the feasibility of the proposed optimization methodology.
