Hierarchical Calibration for Multiunit Generalized Kinematic Errors in Mobile Robotic Machining Systems

Mobile robotic machining systems (MRMS) often suffer from limited overall motion accuracy due to the accumulation and coupling of pose errors among multi-units during operation. To address this issue, this study analyzes the motion transmission chain of MRMS, and decouples the geometric parameter errors and joint compliance errors using the nonsingular line representation method. Subsequently, the linear propagation-decoupling equations for generalized kinematic errors are derived, revealing the transmission mechanisms of different types of errors among various units across coordinate frames. On this basis, an information diffusion-based dataset augmentation method is developed to address the problem of limited sample data, and it is integrated with gradient boosting decision trees to predict the residual uncertainty errors. Furthermore, a hierarchical calibration method is proposed to progressively calibrate joint compliance errors, generalized geometric parameter errors, and residual uncertainty errors of MRMS. The effectiveness and superiority of the proposed method are validated through experiments.