Symmetry-Guided Multi-Objective Structural Optimization of a Heavy-Duty Six-Axis Industrial Robot with Dominant Joint Flexibility

This study presents a symmetry-guided, mechanism-informed, and constraint-aware staged evolutionary framework for the structural optimization of a heavy-duty industrial robot with dominant joint flexibility. Unlike conventional sizing strategies that treat transmission compliance as a secondary verification issue, the proposed method incorporates joint-flexibility-induced low-frequency vibration directly into the optimization formulation and organizes the design problem through a symmetric joint-space/Cartesian-space evaluation framework. An equivalent linearized flexible-joint dynamic model is established for the dominant load-bearing joints under the heavy-load operating condition of interest, and three coordinated performance indices are constructed to characterize vibration robustness, end-effector static stiffness, and global velocity-transmission quality under explicit workspace-retention constraints. To improve engineering interpretability, a staged NSGA-II strategy is adopted, in which global link-length variables and local sectional variables are optimized sequentially. The results indicate that the proposed framework increases the minimum first-order vibration frequency, reduces end-effector deformation, and preserves acceptable workspace coverage. More importantly, the optimization process reveals an interpretable asymmetry in structural sensitivity: sectional redistribution, especially in the forearm, contributes more effectively to vibration suppression than direct reduction in the global arm span. The study therefore provides a reusable symmetry-oriented structural redesign methodology for heavy-duty serial manipulators whose low-frequency dynamics are governed primarily by compliant drive chains.