Comparison of Planar Parallel Manipulator Architectures based on a Multi-objective Design Optimization Approach

TL;DR

This paper compares different planar parallel manipulator architectures using a multi-objective optimization approach focusing on mass, workspace size, dexterity, and stiffness, highlighting their trade-offs.

Contribution

It introduces a systematic comparison of 3-RPR manipulator architectures using Pareto frontiers derived from genetic algorithms.

Findings

3-RPR, 3-RPR, and 3-RPR architectures are compared.

Optimization considers mass, workspace, dexterity, and stiffness.

Pareto frontiers reveal trade-offs among objectives.

Abstract

This paper deals with the comparison of planar parallel manipulator architectures based on a multi-objective design optimization approach. The manipulator architectures are compared with regard to their mass in motion and their regular workspace size, i.e., the objective functions. The optimization problem is subject to constraints on the manipulator dexterity and stiffness. For a given external wrench, the displacements of the moving platform have to be smaller than given values throughout the obtained maximum regular dexterous workspace. The contributions of the paper are highlighted with the study of 3-RPR, 3-RPR and 3-RPR planar parallel manipulator architectures, which are compared by means of their Pareto frontiers obtained with a genetic algorithm.