A new approach to enhance the stiffness of heavy-load parallel robots by means of the component selection

Abstract Stiffness enhancement is one of the most crucial issues for the parallel robots as machine tools. Different from the previous methods including the structural comparison and dimensional synthesis, a new approach to enhance the stiffness of heavy-load parallel robots from the direction of component selection is proposed in this paper. To contain the main parameters of components, an overall stiffness matrix is proposed, where the effects of link deformations and joint clearances are considered. In order to meet the stiffness requirements of the machine tool in practical machining directions, a new stiffness index and an objective function are also derived on the basis of the overall stiffness model. In addition, since the number of component parameters is huge, particle swarm optimization technology is utilized to obtain the appropriate results. Finally, two examples of the A3 head and the Tricept based are presented to demonstrate the practicability of the proposed enhancement approach. According to the results of numerical examples, it shows that the proposed approach is feasible, and it can further enhance the stiffness of parallel robots after the structural comparison and dimensional synthesis.