Wei He’s research while affiliated with Shandong University and other places

Industrial robots are extensively utilized in handling, assembly, and welding tasks owing to their expansive workspace, scalability, flexibility, and cost-effectiveness. However, their inadequate absolute positioning accuracy significantly impedes their application in precise operational scenarios. To enhance robot positioning accuracy, the hysteresis error induced by gear meshing backlash is considered. Firstly, the impact of joint hysteresis on robot positioning errors is analyzed, the notion of modified joint space is introduced, and the similarity theory of error in modified joint space is analyzed. Secondly, for the problem of parameter overfitting of the universal Kriging model, a method of dynamically determining the basis function set by using the genetic algorithm is proposed. Finally, the target trajectory is corrected by a feed-forward iterative compensation algorithm. An experiment on a tandem industrial robot SMART5 NJ 220-2.7 is conducted to demonstrate the effectiveness of the compensation. The experimental results show that the error caused by joint hysteresis is significant, with joint 1 notably affecting y axis positioning accuracy, while joints 2 and 3 predominantly influence x axis positioning accuracy. Furthermore, cross-validation tests verified the good anti-overfitting effect of optimized Kriging for models with multiple input parameters and the good fitting accuracy of the modified space model for hysteresis errors. Moreover, after employing MJS&GPS+GA error modeling and feed-forward iteration compensation, the average absolute positioning error of the trajectory decreased by 81% to 0.09252 mm, and the maximum absolute positioning error decreased by 59% to 0.27713 mm.

The application of robots in high-precision automated machining is constrained by their limited multi-directional repeatability. In contrast, robots demonstrate superior levels of unidirectional repeatability, implying the potential for enhancing their precision. To further improve the positioning accuracy of robots, backlash error induced by rotating direction is considered, the concept of robot joint extended space is proposed, and the robot kinematic model is used to analyze the spatial similarity of robot error in the extended joint space. The dynamic Kriging method based on the optimization of basis functions is proposed to avoid overfitting of the surrogate model, and a model for estimating the robot’s positioning error in the joint extended space is constructed. Based on the estimated positioning error, the proposed calibration method is finally experimentally validated by error feedforward compensation. The results indicate that after Kriging interpolation in the robot joint space and feedforward compensation, the maximum/average positioning error of the robot is improved from 1.5157 mm and 0.8562 mm before compensation to 0.3471 mm and 0.1856 mm after compensation, and then further improved to 0.1848 mm and 0.1197 mm after adopting joint expansion space and dynamic Kriging interpolation, which decreases by 46.7% and 33.5%, respectively. This method effectively compensates the multi-directional repeatability error introduced by the joint backlash and improves the robot’s positioning accuracy.