Research and Application of Robot 3D Hand-Eye Calibration Method Based on Depth Camera Geometric Constraints

To address the issues of high environmental sensitivity, complex operation procedures, insufficient computational efficiency, and inadequate utilization of geometric information in traditional hand-eye calibration methods, this paper proposes a 3D hand-eye calibration method based on depth camera geometric constraints. By designing an asymmetric L-shaped calibration board with orthogonal triangular markers and directly obtaining the 3D coordinates of calibration points using a depth camera, the rigid transformation relationship between the calibration board coordinate system and the camera coordinate system is established based on vector orthogonality constraints. Furthermore, we achieve precise calibration between the camera coordinate system and the robotic arm end-effector coordinate system by solving the AX=XB equation. Experiments were conducted using an Intel RealSense D435i depth camera and a Harmo HM06 six-degree-of-freedom robotic arm. The results show that after calibration, the maximum error between the theoretical and actual values of the feature points is 1.73 mm, which is consistent with the inherent accuracy of the robotic arm. Additionally, the calibration time per session is reduced by 40% compared to traditional methods. This method eliminates the need for complex feature matching and camera extrinsic parameter calibration, significantly enhancing the deployment efficiency and robustness of flexible production lines in industrial settings.