A calibration method for predicting and compensating the flexible positioning errors of a 7-DOF series compliant robot caused by end-effector’s gravity

Abstract

Due to low stiffness of compliant series robot body, the influence of joint flexible deformation caused by the gravity load of the end-effector on the absolute positioning accuracy cannot be ignored. In order to improve the flexible positioning accuracy of the robot end-effector, a calibration method for predicting and compensating the flexible positioning error of the 7-DOF series compliant robot due to the gravity load of the end-effector is proposed. The method identifies and predicts the pose configuration with similar flexible positioning error through the semi-parametric error model based on joint stiffness identification and of BP neural network. The feedforward method is used to compensate the positioning error. In this study, a 7-DOF series compliant robot is selected as the research object. Based on the principle of error similarity, the measurement points and the corresponding pose configurations are selected as the training data for the parameter identification of the semi-parametric error model, and the flexible positioning errors on the continuous trajectory of the end-effector are compensated according to the predicted values of the model. When the mass of the end-effector is 5 kg, by this method, the maximum value, mean value and mean square error of flexible positioning error on multiple straight-line trajectories on the plane are increased from 8.4779, 5.6039, and 1.8496 mm to 0.9720, 0.3079, and 0.2303 mm, respectively. It means the positioning accuracy are increased by 88.53%, 94.50%, and 87.55%, respectively, by which could observe that the precision of this robot’s end-effector was significantly improved.

Keywords

Positioning accuracy flexible deformation stiffness identification error similarity error compensation

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