Dynamic modeling and Multi-Objective Optimization of a 3DOF Reconfigurable Parallel Robot

Abstract

The reconfigurable parallel robots are highly adaptable to different tasks and environments, making them suitable for a wide range of industrial and medical applications. Optimizing the geometrical and structural parameters is a crucial aspect of designing a parallel robot. However, due to different degrees of freedom and workspaces, the optimization of reconfigurable parallel robots is a challenge. This paper presents the design, unified dynamic modeling and multi-objective optimization methodology of an innovative 3UPS-PU/S robot. This parallel robot can be reconfigured from a Tricept mechanism into a fully spherical mechanism through the reconfiguration of the PU/S central passive limb. For this purpose, the unified dynamic model of the robot is derived. With respect to workspace, manipulability and dynamic dexterity, three performance indices are considered as the objective functions. The robot is optimized with respect to the design and geometrical constraints using the non-dominated sorting genetic algorithm II (NSGA-II), which is used to find the Pareto fronts. The obtained solutions are a set of optimal geometric parameters to adjust the kinematic and dynamic performances. The results depict that the process effectively identified a 3UPS-PU/S robot with an efficient dexterous workspace. Also, based on the optimization results a prototype of the robot was fabricated. Overall, this paper provides a novel framework for the multi-objective optimization of reconfigurable parallel robots.