Elasto-dynamic performance evaluation of a 6-DOF hybrid polishing robot based on kinematic modeling and CAE technology. (October 2022)

• Record Type: Journal Article
• Authors: Ma, Yue; Liu, Haitao; Zhang, Mian; Li, Bin; Liu, Qi; Dong, Chenglin
• Is Part Of: Mechanism and machine theory. Volume 176(2022)
• Publication Date: 2022-10
• Subjects: Hybrid robots -- Inverse kinematic model -- Elasto-dynamic performance -- Finite element analysis; Machine theory -- Periodicals; Machinery -- Periodicals; Machines -- Périodiques; Génie mécanique -- Périodiques; Machine theory; Machinery; Periodicals; 621.81
• DOI: 10.1016/j.mechmachtheory.2022.104983
• Languages: English
• ISSNs: 0094-114X

Abstract

Highlights: An inverse kinematic model is formulated for configuration parameter calculation. The FE modeling strategies of substructures and joint subassemblies are presented. The process for updating the FE model of the robot at any configuration is proposed. The accuracy and efficiency of the method is verified by comparison studies. Abstract: By taking a 6-DOF hybrid polishing robot as an example, this paper presents a generalized methodology for elasto-dynamic analysis of hybrid robots in an easy, accurate and rapid manner. The approach can be implemented by three steps: (1) creating an inverse kinematic model for calculating the configuration parameters of the body-fixed frame of each substructure and the coordinates of the joint frames with respect to the reference frame of the fixed platform; (2) building a parameterized Finite Element (FE) model at the home pose by using the modal reduction techniques and Parametric Design Languages (PDL) embedded in the CAE system; (3) driving the FE model to specified poses using the calculated configuration parameters of substructures and coordinates of joint frames in the batch mode, and evaluating the elasto-dynamic performance of the robot over its entire workspace. The merit of this approach lies in that parallel or hybrid robots having different topologies can be modeled without complex mathematical derivation and operation, allowing the lower-order dynamic performance to be rapidly predicted with sufficient accuracy.