Pose Estimation Algorithm of 3C Parts Based on Virtual 3D Sensor for Robot Assembly

Recently, industrial robots turn out to be an urgent need in 3C (Computer, Communication, and Consumer Electronics) products industries that are characterized by dense labor and increasingly high product quality. However, the high dexterity, high complexity, and high precision requirements of the 3C assembly process still keep the robots out. One of the key issues is how to obtain the high accuracy pose (position and orientation) estimation of the assembly parts, which possess few features. In terms of 3C assembly applications, a pose estimation algorithm that takes point clouds as the data source to estimate the pose of the assembly parts is proposed in this paper. Given the CAD model of the target object, a virtual 3D sensor method is used to generate a virtual 3D view from any viewpoint around the CAD model’s point cloud. Then an ICP based particle filtering method, which takes the generated virtual 3D view as a reference, is carried out to perform the point cloud registration process. The pose estimation method proposed in this paper is validated by simulation and experiments.