4.6 Article

Comparison of Parallel Kinematic Machines with Three Translational Degrees of Freedom and Linear Actuation

Journal

CHINESE JOURNAL OF MECHANICAL ENGINEERING
Volume 28, Issue 4, Pages 841-850

Publisher

SPRINGEROPEN
DOI: 10.3901/CJME.2015.0128.052

Keywords

parallel kinematic machines; comparison; benchmark; selection scheme

Ask authors/readers for more resources

The development of new robot structures, in particular of parallel kinematic machines(PKM), is widely systematized by different structure synthesis methods. Recent research increasingly focuses on PKM with less than six degrees of freedom(DOF). However, an overall comparison and evaluation of these structures is missing. In order to compare symmetrical PKM with three translational DOF, different evaluation criteria are used. Workspace, maximum actuation forces and velocities, power, actuator stiffness, accuracy and transmission behavior are taken into account to investigate strengths and weaknesses of the PKMs. A selection scheme based on possible configurations of translational PKM including different frame configurations is presented. Moreover, an optimization method based on a genetic algorithm is described to determine the geometric parameters of the selected PKM for an exemplary load case and a prescribed workspace. The values of the mentioned criteria are determined for all considered PKM with respect to certain boundary conditions. The distribution and spreading of these values within the prescribed workspace is presented by using box plots for each criterion. Thereby, the performance characteristics of the different structures can be compared directly. The results show that there is no best PKM. Further inquiries such as dynamic or stiffness analysis are necessary to extend the comparison and to finally select a PKM.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.6
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available