Spatial Stiffness Identification and Pose Optimization Analysis of Robotic Milling Process Considering Bidirectional Weak-stiffnesses Characteristic

doi:10.3901/JME.2025.23.308

Abstract

Abstract: Robotic internal cavity milling of complex light alloy thin-walled cabin castings is a new method for thinning cabin parts. The weak stiffness of both the thin-walled parts and the robotic system results in spatial distribution characteristics of the equivalent stiffness during milling. This leads to poor consistency in the dimensional accuracy of the processed workpieces. Establishing an accurate spatial stiffness identification method and characterization model for the robotic milling system is crucial for precision control. A mathematical characterization model for the spatial stiffness of the workpiece-tool-spindle-robot system is introduced. The model is based on the improved Denavit-Hartenberg (D-H) method and the discrete simulation of the milling process, which can comprehensively consider the bidirectional deformation effects of the milling system-workpiece under the action of milling forces. Additionally, a high-fidelity finite element simulation model of the robotic milling system is established. Using this model, a joint stiffness identification method for the robotic system under multiple pose loading inputs is proposed, achieving accurate characterization of the spatial stiffness of the multi-axis robotic system. Considering the stiffness distribution characteristics within themotion space, pose analysis and experimental verification of the robotic milling processing system are conducted. These are based on the milling characteristics of the inner cavity of the cylindrical cabin. The results demonstrate that the high-fidelity finite element simulation model of the workpiece-tool-spindle-robot system enables spatial stiffness analysis of the milling system-workpiece during machining. This improves the joint stiffness identification accuracy of the robotic system, thereby enhancing the spatial machining accuracy of the robotic milling system and the accuracy of the workpiece contour.

Key words: robotic milling, bidirectional weak-stiffness, stiffness identification, pose optimization, digital twin

CLC Number:

TP242

GU Qunfei, LIU Shun, JIN Sun. Spatial Stiffness Identification and Pose Optimization Analysis of Robotic Milling Process Considering Bidirectional Weak-stiffnesses Characteristic[J]. Journal of Mechanical Engineering, 2025, 61(23): 308-320.

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