Calibration of multi-robot coordinates for collaborative wire arc additive manufacturing using cross-source 3D point cloud models

Abstract

To increase the deposition deficiency and extend the working range of a single actuator, multi-robot collaborative wire arc additive manufacturing (MRC-WAAM) is proliferating in industry. Implementing an MRC-WAAM system should ensure precise transformations between a part frame and multiple robot work frames (RWFs) to facilitate fabrication quality. This paper proposes a novel calibration method for calculating the spatial correlation of RWFs by registering readings of multiple robot-carried 3D sensors. After formulating the influence of both translational and rotational errors, the principles and implementation are presented. To deal with the heterogeneity of cross-source point cloud models, an improved iterative closest point algorithm is articulated. The results of validation show that the proposed method can achieve high accuracy in orientation consistency of RWFs with an error of 0.091 deg, which is superior to the current state-of-the-art. This method can alleviate the consequences caused by the inconformity of multi-robot frames.