Pose Estimation of 3C Components Based on Monocular 2D Camera In order to accurately and effectively estimate the pose of 3C product components in the manufacturing process and meet the needs of intelligent production, this paper proposes a complete 3C component pose estimation technology scheme based on the Perspective nPoints algorithm, and also analyzes and verifies the impact of errors in theoretical derivation and experiment. Showing in the framework, firstly, we compared common monocular camera pose estimation algorithms to choose the suitable one, identified and analyzed the factors affecting the accuracy of pose estimation, then the whole design of marker points is discussed and the corresponding image detection and localization algorithm is optimized. After completing the above theoretical analysis and realization, an accomplished technical workflow is formed. Through 3D software simulation and actual experiment, the effectiveness and accuracy of the pose estimation scheme in monocular camera case are verified, and the theoretical basis for realizing the higher precision in multicamera case is also provided.

Pose estimation of components in 3C products based on point cloud registration In order to meet the industrial highprecision assembly requirement for components in 3C products, which is textureless and highly symmetrical, a noncontact pose estimation scheme based on point cloud registration is proposed. The scheme use global registration to quickly find the initial coarse pose of the 3C assembly relative to the camera. Considering the singularity problem caused by the high symmetry of the components in 3C products, templatebased algorithm is introduced to eliminate the singular pose, then local registration is used to improve the accuracy of the initial pose based on the global registration result. In order to avoid the local registration algorithm falling into local optimum due to insufficient accuracy of the initial pose, we use improved Globally Optimal Iterative Closest Point (GoICP) to performs a finer search in the small space including the global optimal pose. The reliability and effectiveness of the scheme are verified by simulation and experiments.