Manipulator-based machine tending is a key automation technology in computer numerical control (CNC) machining, and mobile-base configurations are increasingly adopted to enable flexible reconfiguration in high-mix, low-volume manufacturing environments. However, once the robot base is relocated, the previously taught trajectory is no longer valid, and manual reteaching is required, which is time-consuming, labor-intensive, and highly dependent on operator skill. This paper proposes a marker-based machine tending method that combines multi-marker Perspective-n-Point (PnP) pose estimation with Iterative Closest Point (ICP) registration in a two-step calibration. In the first step, PnP is used to move the robot to the pre-stored reference pose. In the second step, ICP is applied to the point cloud data obtained at the current robot pose and the pre-stored point cloud data to estimate the change in the robot base pose with respect to the CNC machine. Based on this estimate, the robot can resume its task after base relocation. Validation in a CNC lathe machine tending environment showed that, compared with conventional marker-only calibration, the position repeatability measured by a laser tracker improved from 2.658 to 1.795 mm and the machine tending success rate increased from 47% to 93%, confirming the effectiveness of the proposed method.
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