A general approach for robot pose error compensation based on an equivalent joint motion error model

• A general error model from the perspective of linear space is proposed. • It is established based on screw theory (basis) and power series method (coordinates). • Pose error is decoupled into joint space to improve the identification efficiency and accuracy. • Statistic index with dimensional homogeneity is proposed to evaluate the effectiveness of identification and compensation. • Changes in indices corresponding to different model orders with noise are analyzed. A general error modelling, measurement, and compensation approach for robot calibration was proposed based on the equivalent joint motion error model from the perspective of vector space. First, the end pose error was expressed as a linear combination of the twists and the equivalent motion errors of the actuated joints, and the latter were described as functions of the ideal configuration. On this basis, the pose error in operating space was decoupled in joint space, and the regression model corresponding to each actuated joint was established. Then, a statistical index with dimensional consistency was proposed to evaluate the predictive capability of the model, and the variation of the prediction accuracy in the presence of system noise was studied. Finally, experiments were conducted adopting the strategy of off-line identification and on-line compensation. After calibration, the average value of robot position and attitude errors can be reduced to 0.046 mm and 0.011 deg, respectively.