Optimal design of a spherical parallel manipulator based on kinetostatic performance using evolutionary techniques

Abstract

This study aims to provide an optimal design for a Spherical parallel manipulator (SPM), namely, the Agile Eye. This aim is approached by investigating kinetostatic performance and workspace and searching for the most promising design. Previously recommended designs are examined to determine whether they provide acceptable kinetostatic performance and workspace. Optimal designs are provided according to different kinetostatic performance indices, especially kinematic sensitivity. The optimization process is launched based on the concept of the genetic algorithm. A single-objective process is implemented in accordance with the guidelines of an evolutionary algorithm called differential evolution. A multi-objective procedure is then provided following the reasoning of the nondominated sorting genetic algorithm-II. This process results in several sets of Pareto points for reconciliation between kinetostatic performance indices and workspace. The concept of numerous kinetostatic performance indices and the results of optimization algorithms are elaborated. The conclusions provide hints on the provided set of designs and their credibility to provide a well-conditioned workspace and acceptable kinetostatic performance for the SPM under study, which can be well extended to other types of SPMs.