Hybrid 3D Model Based Tracking and Registration for Guided Maintenance

In guided maintenance systems, the 3D model based registration algorithm requires user assisted initial pose, is prone to drift error, and cannot automatically update the 3D model, when tracking complex mechanical objects. To address these issues, a hybrid edge-based 3D registration and tracking is proposed. it uses the particle filter algorithm to set the number of edge pixels as a criterion and initialize the pose of camera. In the later continuous pose estimation, it adopts a nonlinear least square method to update the poses, and eliminates error drifting by real-time monitoring the number of control points on the model. The proposed algorithm achieves the process recognition by key-point matching to finally get an auto-updating 3D model. The experimental results on the prototype system show that the proposed algorithm is robust and efficient, and effectively eliminates error drifting at the same time.