Monocular Depth-Based Object Localization for Collaborative Robotic Grasping

This paper investigates the application of monocular depth estimation for 3D object localization in collaborative robotic manipulation tasks. We propose a method for converting relative depth maps obtained using the Depth Anything V2 Small model into metric depth maps by employing small 5 × 5 cell ArUco markers with a physical size of 3 × 3 cm, which do not obstruct the operator or reduce the available workspace. Pre-calibration on 10–30 images achieves a diameter measurement accuracy with a mean absolute error (MAE) of 0.307–0.671 cm (relative error 3.6–7.9