Automatic multi-stereo-vision reconstruction method of complicated tubes for industrial assembly

2016 ◽  
Vol 36 (4) ◽  
pp. 362-375 ◽  
Author(s):  
Peng Jin ◽  
Jian Hua Liu ◽  
Shao Li Liu ◽  
Xiao Wang
Keyword(s):  
Stereo Vision ◽  
Measurement Method ◽  
Automatic Measurement ◽  
Point Clouds ◽  
Geometric Error ◽  
Reconstruction Method ◽  
Control Points ◽  
Content Type ◽  
Measurement Results ◽  
Adjacent Line

Purpose Complicated tubes extensively exist in the industrial equipment. The manufacturing precision of the tubes is difficult to be ensured with bending machine. Therefore, the tubes’ 3D geometric error should be fixed according to measurement results. However, there are no convenient methods to accomplish the measurement accurately and effectively. Thus, this paper aims to propose a new tube measurement method to achieve tube's automatic measurement. The accurate measurement results can be used to fix the geometric error of the tube to achieve stress-free assembly. Design/methodology/approach Tubes’ shape can be determined by control points. First, the point clouds of the centre line by multi-stereo-vision technology are reconstructed. Then, the point clouds to the spine of the tube are thinned by moving least-squares and segmented into lines and arcs. Finally, the control points are calculated and the model is reconstructed. The authors can get the tube’s geometric dimensions from the model. Findings The experiment results indicate that the multi-stereo-vision technology can solve the occlusion problem and measure the complicated tubes efficiently and accurately. Originality/value The paper proposed a tube measurement method. The repeatability measuring precision was 0.12 mm, and the absolute measuring precision was within 0.78 mm. The tube spectra assessed in this paper are in the range of angles between two adjacent line segments of 3-177° and the shortest length of the line segment is greater than 5 mm, confirming that the proposed algorithm can measure various complicated tubes effectively and accurately.

Accurate profile measurement method for industrial stereo-vision systems

Sensor Review ◽  
2020 ◽  
Vol 40 (4) ◽  
pp. 445-453
Author(s):  
Yang Zhang ◽  
Wei Liu ◽  
Yongkang Lu ◽  
Xikang Cheng ◽  
Weiqi Luo ◽  
...  
Keyword(s):  
Stereo Vision ◽  
Measurement Method ◽  
Vision System ◽  
Practical Implication ◽  
Image Features ◽  
Reference Points ◽  
Profile Measurement ◽  
Surface Boundary ◽  
Content Type ◽  
Profile Reconstruction

Purpose Profile measurement with boundary information plays a vital role in the detection of quality in the assembly of aviation parts. The purpose of this paper is to improve the evaluation accuracy of the aerodynamic shapes of airplanes, the profiles of large-sized parts need to be measured accurately. Design/methodology/approach In this paper, an accurate profile measurement method based on boundary reference points is proposed for the industrial stereo-vision system. Based on the boundary-reference points, the authors established a priori constraint for extracting the boundary of the measured part. Combining with the image features of background and the measured part, an image-edge compensation model is established to extract the boundary of the measured part. The critical point of a laser stripe on the edge of the measured part is extracted corresponding to the boundary constraint. Finally, as per the principle of binocular vision, the profile of the measured part is reconstructed. Finding Laboratory experiments validate the measurement accuracy of the proposed method which is 0.33 mm. In the analysis of results between the measured data and the theoretical model, the measuring accuracy of the proposed method was found to be significantly higher than that of the other traditional methods. Practical implication An aviation part was measured in the part-assembly shop by the proposed method, which verified the feasibility and effectiveness of this method. The research can realize the measurement of smooth surface boundary which can solve existing profile reconstruction problems for aviation parts. Originality/value According to the two-dimensional contour constraint, critical points of the laser strip sequence at the edge of measured part are extracted and the accurate profile reconstruction with the boundary is realized.

scholarly journals Canopy Parameter Estimation of Citrus grandis var. Longanyou Based on LiDAR 3D Point Clouds

2021 ◽  
Vol 13 (9) ◽  
pp. 1859
Author(s):  
Xiangyang Liu ◽  
Yaxiong Wang ◽  
Feng Kang ◽  
Yang Yue ◽  
Yongjun Zheng
Keyword(s):  
Convex Hull ◽  
Clustering Algorithm ◽  
Plant Protection ◽  
Point Clouds ◽  
Biomass Estimation ◽  
Reconstruction Method ◽  
Volume Calculation ◽  
Alpha Shape ◽  
3D Point Clouds ◽  
Canopy Volume

The characteristic parameters of Citrus grandis var. Longanyou canopies are important when measuring yield and spraying pesticides. However, the feasibility of the canopy reconstruction method based on point clouds has not been confirmed with these canopies. Therefore, LiDAR point cloud data for C. grandis var. Longanyou were obtained to facilitate the management of groves of this species. Then, a cloth simulation filter and European clustering algorithm were used to realize individual canopy extraction. After calculating canopy height and width, canopy reconstruction and volume calculation were realized using six approaches: by a manual method and using five algorithms based on point clouds (convex hull, CH; convex hull by slices; voxel-based, VB; alpha-shape, AS; alpha-shape by slices, ASBS). ASBS is an innovative algorithm that combines AS with slices optimization, and can best approximate the actual canopy shape. Moreover, the CH algorithm had the shortest run time, and the R2 values of VCH, VVB, VAS, and VASBS algorithms were above 0.87. The volume with the highest accuracy was obtained from the ASBS algorithm, and the CH algorithm had the shortest computation time. In addition, a theoretical but preliminarily system suitable for the calculation of the canopy volume of C. grandis var. Longanyou was developed, which provides a theoretical reference for the efficient and accurate realization of future functional modules such as accurate plant protection, orchard obstacle avoidance, and biomass estimation.

Robust-PCA-based hierarchical plane extraction for application to geometric 3D indoor mapping

2014 ◽  
Vol 41 (2) ◽  
pp. 203-212 ◽  
Author(s):  
Suyong Yeon ◽  
ChangHyun Jun ◽  
Hyunga Choi ◽  
Jaehyeon Kang ◽  
Youngmok Yun ◽  
...  
Keyword(s):  
Principal Component ◽  
Point Clouds ◽  
Previous Method ◽  
Divide And Conquer ◽  
Sensor Data ◽  
Estimation Accuracy ◽  
Content Type ◽  
Extraction Algorithm ◽  
Plane Extraction ◽  
Scan Data

Purpose – The authors aim to propose a novel plane extraction algorithm for geometric 3D indoor mapping with range scan data. Design/methodology/approach – The proposed method utilizes a divide-and-conquer step to efficiently handle huge amounts of point clouds not in a whole group, but in forms of separate sub-groups with similar plane parameters. This method adopts robust principal component analysis to enhance estimation accuracy. Findings – Experimental results verify that the method not only shows enhanced performance in the plane extraction, but also broadens the domain of interest of the plane registration to an information-poor environment (such as simple indoor corridors), while the previous method only adequately works in an information-rich environment (such as a space with many features). Originality/value – The proposed algorithm has three advantages over the current state-of-the-art method in that it is fast, utilizes more inlier sensor data that does not become contaminated by severe sensor noise and extracts more accurate plane parameters.

Robotic motion compensation for bone movement, using ultrasound images

2015 ◽  
Vol 42 (5) ◽  
pp. 466-474 ◽  
Author(s):  
P.M.B. Torres ◽  
P. J. S. Gonçalves ◽  
J.M.M. Martins
Keyword(s):  
Motion Compensation ◽  
Optical Measurement ◽  
Three Dimensional ◽  
Point Clouds ◽  
Robotic System ◽  
Ultrasound Images ◽  
Bone Drilling ◽  
Content Type ◽  
3D Point Clouds ◽  
Robotic Motion

Purpose – The purpose of this paper is to present a robotic motion compensation system, using ultrasound images, to assist orthopedic surgery. The robotic system can compensate for femur movements during bone drilling procedures. Although it may have other applications, the system was thought to be used in hip resurfacing (HR) prosthesis surgery to implant the initial guide tool. The system requires no fiducial markers implanted in the patient, by using only non-invasive ultrasound images. Design/methodology/approach – The femur location in the operating room is obtained by processing ultrasound (USA) and computer tomography (CT) images, obtained, respectively, in the intra-operative and pre-operative scenarios. During surgery, the bone position and orientation is obtained by registration of USA and CT three-dimensional (3D) point clouds, using an optical measurement system and also passive markers attached to the USA probe and to the drill. The system description, image processing, calibration procedures and results with simulated and real experiments are presented and described to illustrate the system in operation. Findings – The robotic system can compensate for femur movements, during bone drilling procedures. In most experiments, the update was always validated, with errors of 2 mm/4°. Originality/value – The navigation system is based entirely on the information extracted from images obtained from CT pre-operatively and USA intra-operatively. Contrary to current surgical systems, it does not use any type of implant in the bone to track the femur movements.

A depth camera-based full-body reconstruction method for body pose training in occupational safety

2020 ◽  
Vol 64 (1) ◽  
pp. 1541-1545
Author(s):  
Li Li ◽  
Ken Chen ◽  
Karen Chen ◽  
Xu Xu*
Keyword(s):  
Occupational Injuries ◽  
Technological Development ◽  
Point Clouds ◽  
Incidence Rates ◽  
Multiple Point ◽  
Reconstruction Method ◽  
Safety Education ◽  
Depth Cameras ◽  
Work Related ◽  
Full Body

Occupational injuries have high incidence rates across various industries. Safety education is a key component to effectively reduce work-related injuries. Posture training for work safety is widely adopted to increase the awareness of unsafe movements at work and to evaluate workers to minimize work-related musculoskeletal stresses. However, existing one-size-fits-all pamphlet-based posture training is facing challenges in its effectiveness. In recent years, the substantial technological development in virtual reality (VR) and augmented reality (AR) has made immersive and personalized education possible. For VR/AR-assisted posture training, full-body reconstruction from multiple point clouds is the key step. In this study, we propose a fast and coarse method to reconstruct the full-body pose of safety instructors using multiple low-cost depth cameras. The reconstructed body images from depth cameras are registered through iterative closet point algorithm. The reconstructed full-body pose can be further rendered in VR/AR environments for next-generation safety education.

Obstacle detection based on depth fusion of lidar and radar in challenging conditions

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Guotao Xie ◽  
Jing Zhang ◽  
Junfeng Tang ◽  
Hongfei Zhao ◽  
Ning Sun ◽  
...  
Keyword(s):  
False Alarm ◽  
Experimental Tests ◽  
Point Clouds ◽  
Calibration Method ◽  
Obstacle Detection ◽  
Environmental Perception ◽  
Fusion Model ◽  
Content Type ◽  
Self Calibration ◽  
Temporal Relationships

Purpose To the industrial application of intelligent and connected vehicles (ICVs), the robustness and accuracy of environmental perception are critical in challenging conditions. However, the accuracy of perception is closely related to the performance of sensors configured on the vehicle. To enhance sensors’ performance further to improve the accuracy of environmental perception, this paper aims to introduce an obstacle detection method based on the depth fusion of lidar and radar in challenging conditions, which could reduce the false rate resulting from sensors’ misdetection. Design/methodology/approach Firstly, a multi-layer self-calibration method is proposed based on the spatial and temporal relationships. Next, a depth fusion model is proposed to improve the performance of obstacle detection in challenging conditions. Finally, the study tests are carried out in challenging conditions, including straight unstructured road, unstructured road with rough surface and unstructured road with heavy dust or mist. Findings The experimental tests in challenging conditions demonstrate that the depth fusion model, comparing with the use of a single sensor, can filter out the false alarm of radar and point clouds of dust or mist received by lidar. So, the accuracy of objects detection is also improved under challenging conditions. Originality/value A multi-layer self-calibration method is conducive to improve the accuracy of the calibration and reduce the workload of manual calibration. Next, a depth fusion model based on lidar and radar can effectively get high precision by way of filtering out the false alarm of radar and point clouds of dust or mist received by lidar, which could improve ICVs’ performance in challenging conditions.

Block Thickness Measurement of Using the Structured Light Vision

2018 ◽  
Vol 33 (01) ◽  
pp. 1955001 ◽  
Author(s):  
Fenghui Lian ◽  
Qingchang Tan ◽  
Siyuan Liu
Keyword(s):  
Machine Vision ◽  
Measurement Method ◽  
Measurement Accuracy ◽  
Thickness Measurement ◽  
Base Plane ◽  
Vision Measurement ◽  
Measurement Results ◽  
Measurement Equations ◽  
Structured Light Vision ◽  
Measuring Base

A method for measuring block thicknesses is proposed by the machine vision measurement. Equations of the measuring base plane and the light plane are formed by calibration. Then, the equation of the light strip image, that is, the image of the intersection between the base plane and light one, is established by the projection relation. Equation of the image of the light strip on the measured plane can be determined by the fitting. Since the light strip on the measuring base plane is parallel to one on the measured plane, the thickness of the measuring block is measured by using the two equations. The experiment evaluates the measurement accuracy of the measurement method and analyzes the influence of some factors on the measurement results.

scholarly journals Measurement experiences with FluxSet digital D/I station

2017 ◽  
Vol 6 (2) ◽  
pp. 279-284 ◽  
Author(s):  
László Hegymegi ◽  
János Szöllősy ◽  
Csaba Hegymegi ◽  
Ádám Domján
Keyword(s):  
Measurement Method ◽  
Measurement Data ◽  
Digital Form ◽  
New Instrument ◽  
Measurement Results ◽  
Inclination Angles ◽  
Flux Gate

Abstract. Geomagnetic observatories use classical theodolites equipped with single-axis flux-gate magnetometers known as declination–inclination magnetometers (DIM) to determine absolute values of declination and inclination angles. This instrument and the measurement method are very reliable but need a lot of handwork and experience. The authors developed and built a non-magnetic theodolite which gives all measurement data in digital form. Use of this instrument significantly decreases the possibility of observation errors and minimises handwork. The new instrument is presented in this paper together with first measurement results in comparison to the classical DIM.

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