A minimal-error-model based two-step kinematic calibration methodology for redundantly actuated parallel manipulators: An application to a 3-DOF spindle head. (January 2022)

• Record Type: Journal Article
• Authors: Jiang, Shujia; Chi, Changcheng; Fang, Hanliang; Tang, Tengfei; Zhang, Jun
• Is Part Of: Mechanism and machine theory. Volume 167(2022)
• Publication Date: 2022-01
• Subjects: Kinematic calibration -- Error modeling -- Sensitivity analysis -- Error identification -- Redundantly actuated parallel manipulator; Machine theory -- Periodicals; Machinery -- Periodicals; Machines -- Périodiques; Génie mécanique -- Périodiques; Machine theory; Machinery; Periodicals; 621.81
• DOI: 10.1016/j.mechmachtheory.2021.104532
• Languages: English
• ISSNs: 0094-114X

Abstract

Highlights: l A set of principles of eliminating redundant geometric source errors in RAPMs is proposed. l An kinematic error model including least number of geometric source errors is established for RAPMs. l A hierarchical-error-identification based two-step kinematic calibration methodology is proposed for RAPMs. Abstract: Zero offsets and geometric source errors will significantly degrade the kinematic accuracy of redundantly actuated parallel manipulators (RAPMs). To relieve the influences of these factors, this paper presents a minimal-error-model based two-step kinematic calibration methodology for this type of parallel manipulators. A novel 3-DOF spindle head with a 2UPR&2RPS topology is taken as an example to demonstrate the kinematic calibration methodology. The proposed kinematic calibration methodology includes three critical steps: (1) a set of general principles is proposed to eliminate redundant geometric source errors in the manipulator to derive a minimal error model that includes the least number of geometric source errors; (2) a sensitivity analysis is carried out using the Monte-Carlo simulation to reveal the relative impact of geometric source errors on the terminal accuracy; (3) a hierarchical identification strategy composed of a coarse identification and a fine identification is proposed, based on which a two-step calibration methodology is constructed. Finally, a set of calibration experiments is performed to verify the effectiveness of the proposed calibration methodology.