Papers by Keyword: ICP

Paper TitlePage

Authors: Chao Chen, Yan Li, Wei Wang
Abstract: This paper proposes a 3D point cloud registration method based on light detection and ranging (LiDAR) system. The proposed method consists of three steps: Gaussian-Process based ground segmentation, a novel k-neighbors based dynamic point feature and Iterative Closest Point (ICP) fine registration. The first two steps are the preparation of ICP fine registration. The odometry information from a GPS/IMU system is used to compensate the vehicle's ego-motion. The Gaussian-Process based ground segmentation is adopted to remove ground points. A novel Initial Localization based Dynamic Feature (ILDF) is proposed to detect and remove dynamic points. It is applicable in sequential frames and a proper initial localization without a large dislocation. In experiment results, a large number of dynamic points will be detected and removed by ILDF. The removal of dynamic points improves both accuracy and efficiency of registration algorithm.
365
Authors: Li Cheng Fan, Feng Feng Zhang
Abstract: The measurement of the teeth surface and the CAD modeling of the point cloud data are the key basics for the following CNC machining, and the complete data can only be obtained through multi-perspective scanning method. Using ICP iteration algorithm that based on point-to-line to the multi-perspective scanning data, specific to the features of layering scanning, retrograde the 3D data registration to 2D planar registration, and provide the cutting and splicing algorithm for registered tooth data, obtain precise and integrated tooth surface point cloud data, which serves as the CAD model for the following CNC machining.
111
Authors: Shi Jun He, Shi Ting Zhao, Fan Bai, Jia Wei
Abstract: The spatial data which acquired by 3D laser scanning is huge, aiming at the iteration time is long with classic ICP algorithm, a improved registration algorithm of spatial data ICP algorithm which based on principal component analysis (PCA) is proposed in this paper (PCA-ICP), the basic principle and steps of PCA-ICP algorithm are given. The experiment results show that this method is feasible and the iterative time of PCA-ICP algorithm is shorter than classical ICP algorithm.
1033
Authors: Guan Guan, Mei Shen, Yan Lin, Zhuo Shang Ji
Abstract: The deviation analysis of hull construction is a common problem in shipbuilding. In this paper, we present an automatic registration method of hull blocks points measured by Total Station based on principal component analysis (PCA) and the iterative closest point (ICP) algorithm. The method is divided into two steps. The first step rough registration based on PCA can narrow the dislocation between measurement points and CAD model points giving closed initialization. The second step refined registration based on ICP can obtain the optimal solution. The algorithm can automatically match measurement data with CAD model without prior information on transformation. We have applied this method to the registration of the Hull Block Point Clouds in a bulk carrier. Our result shows that the algorithm works efficiently.
3089
Authors: Li Zhao Liu, Xiao Jing Hu, Yu Feng Chen, Tian Hua Zhang, Mao Qing Li
Abstract: The paper proposed a original matching algorithm using the feature vectors of rigid points sets matrix and a online matching intersection testing algorithm using the bounding sphere. The relationship searching between points in each set is took place by the corresponding eigenvectors that is a closed form solution relatively. The affine transformed eigenvalue and eigenvector is also used instead of the affine transformed points sets for the non-rigid matching that do not need the complicated global goal function. The characteristics matching for the initial registration can give a well initial value for the surfaces align that improve the probability of global solution for the following-up ICP
287
Authors: Jian Chuan Li, Jian Feng Yu
Abstract: During the process of aircraft wing finish machining, it is required to calculate the posture of aircraft wing to guide its adjustment. This paper proposes a new method to calculate the posture for aircraft wing finishing machining, through analyzing the level-measuring principle of aircraft wing. The proposed method is based on the iterative closest point algorithm (ICP), which transforms the posture evaluation problem into a registration problem between space points and surface. It repeats two processes, finding the nearest points and calculating the optimal transformation, until the convergence criteria of correctly matching are well satisfied. It also has an important part matching priority so that it could satisfy the different accuracy requirements of different metrical points. A case is presented to validate the proposed method, and the results suggest its feasibility.
1279
Authors: Matthias Schweinoch, Alexei Sacharow, Dirk Biermann, Christoph Buchheim
Abstract: Springback effects, as occuring in sheet metal forming processes, pose a challenge to manufacturingplanning: the as-built part may deviate from the desired shape rendering it unusable forits intended purpose. A compensation can be achieved by modifying the forming tools to counteractthe shape deviations. A prerequisite to compensation is the knowledge of correspondences (ui; vj),between points ui on the desired and vj on the actual shape. FEM-based simulation software providesmeans to both virtually predict springback and directly obtain correspondences. In case of experimentalprototyping and validation, however, finding correspondences requires solving a registrationproblem: given a test shape Q (scan points of the as-built geometry) and a reference shape R (CADdata of the desired geometry), a transformation S has to be found to fit both objects. Correspondencesbetween S(Q) and R may then be computed based on a metric.If S is restricted to Euclidean transformations, then S(Q) results in a rigid transformation, whereevery point of Q is subject to the same translation and rotation. Local geometric deviations due tospringback are not considered, often resulting in invalid correspondences. In this contribution, a nonrigidregistration method for the efficient analysis of springback is therefore presented. The test shape Q is iteratively partitioned into segments with respect to an error metric. The segments are locally registeredusing rigid registration subject to regulatory conditions. Resulting discontinuities are addressedby minimization of the deformation energy. The error metric uses information about the deviationscomputed based on the correspondences of the previous iteration, e.g. maximum errors or changes ofthe sign. This adaptive per-segment registration allows appropriate correspondences to be determinedeven under local geometric deviations.
1015
Authors: Ireneusz Wróbel
Abstract: Reverse engineering [ is a field of technology which has been under rapid development for several recent years. Optic scanners are basic devices used as reverse engineering tools. Point cloud describes the shape of a scanned object. Automatic turntable is a device which enables a scanning process from different viewing angles. In the paper, the algorithm is described which has been used for determination of rotation axis of a turntable. The obtained axis constitutes the base for an aggregation of particular point clouds into single resultant common cloud describing the shape of the scanned object. Usability of this algorithm for precise scanning of mechanical parts was validated, precision of shape replication was also evaluated.
273
Authors: Wen Chung Chang, Chia Hung Wu
Abstract: In this research, an automated robotic bin-picking system employing active vision for picking up randomly distributed plumbing parts is presented. This system employs an actively-controlled single eye-in-hand system to observe structured light projected onto a set of plumbing parts in a bin. By using image processing and iterative closest point (ICP) algorithms, a single plumbing part that could possibly be taken from the bin is detected. Specifically, by projecting stationary structured light patterns onto the set of plumbing objects, the features on the surfaces of plumbing parts can be reconstructed by actively moving the eye-in-hand camera while performing visual tracking of those features. An effective 3D segmentation technique is employed to extract the point cloud of a single plumbing part that can possibly be grasped successfully. Once the object point cloud is obtained, one needs to determine the coordinate transformation from the end-effector to the selected plumbing part for grasping motion. With the point cloud matching result based on utilizing the ICP algorithm, the position and orientation of the selected plumbing part can be correctly estimated if the deviation of the object point cloud from the model point cloud is small. The control command can thus be given to the robotic manipulator to accomplish the automated bin-picking task. To effectively expand the allowed deviation of the object point cloud, an approximate pose estimation algorithm is employed before performing the ICP algorithm. The proposed approach can virtually estimate any pose of the plumbing part and has been successfully experimented with an industrial manipulator equipped with eye-in-hand single-camera vision and a LCD projector fixed in the work space demonstrating the feasibility and effectiveness. The proposed automated bin-picking system appears to be cost-effective and have great potentials in industrial factory automation applications.
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