scholarly journals A path planning method for a surface inspection system based on two-dimensional laser profile scanner

2019 ◽  
Vol 16 (4) ◽  
pp. 172988141986246 ◽  
Author(s):  
Lina Li ◽  
De Xu ◽  
Linkai Niu ◽  
Yuan Lan ◽  
Xiaoyan Xiong
Keyword(s):  
Path Planning ◽  
Three Dimensional ◽  
Neighborhood Search ◽  
Inspection System ◽  
Two Dimensional ◽  
Surface Data ◽  
Scanning Path ◽  
Scanning Path Planning ◽  
Robot Position ◽  
Orientation Determination

In this article, a method for two-dimensional scanning path planning based on robot is proposed. In this method, a section division algorithm based on neighborhood search method for scanning orientation determination is firstly produced. The scanning paths which meet constraints of the system are then generated. Finally, the experiment is carried out on robot-based scanning platform. The two-dimensional data from scanner and the robot position are combined to form three-dimensional surface data of measured workpiece. The experiment results verify the effectiveness of proposed method.

Scanning Path Planning in Laser Bending of Tube Based on Curvature

2011 ◽  
Vol 264-265 ◽  
pp. 6-11
Author(s):  
Xu Yue Wang ◽  
Jun Wang ◽  
L.J. Wang ◽  
W.J. Xu ◽  
D.M. Guo
Keyword(s):  
Path Planning ◽  
Extreme Point ◽  
Dimensional Space ◽  
Three Dimensional ◽  
Two Dimensions ◽  
Two Dimensional ◽  
Laser Bending ◽  
Scanning Path ◽  
Scanning Path Planning ◽  
Three Dimensional Space

A method is presented based on geometric-curvature characteristics in which a scanning path planning for laser bending of a straight tube into a curve tube in a two- and three-dimensional space. In a two-dimensional (plane) bending, the steel tube is divided into several segments according to the extreme point and inflection point of the desired shape of the tube, taking the extreme point as the initial place of the path planning, using different scanning space for every segment in order to identify the scanning paths. For a tube bending in a three-dimensional space, a projection decomposition method is used, where the three-dimensional is decomposed into two two-dimensions, and respective scanning path planning and process parameters are thus acquired. By combining the data in the two-dimensional planes, the three-dimensional scanning path plan was obtained. Finally, an experimental verification is carried out to bend straight tubes into a two-dimensional sinusoidal and a three-dimensional helical coil-shaped tube. The results show that the proposed method of scanning path planning is effective and feasible.

scholarly journals Research Progress of Automated Visual Surface Defect Detection for Industrial Metal Planar Materials

Sensors ◽  
2020 ◽  
Vol 20 (18) ◽  
pp. 5136
Author(s):  
Xiaoxin Fang ◽  
Qiwu Luo ◽  
Bingxing Zhou ◽  
Congcong Li ◽  
Lu Tian
Keyword(s):  
Defect Detection ◽  
Surface Defect ◽  
Three Dimensional ◽  
Image Features ◽  
Stereoscopic Vision ◽  
Research Progress ◽  
Inspection System ◽  
Two Dimensional ◽  
Surface Defect Detection ◽  
Planar Materials

The computer-vision-based surface defect detection of metal planar materials is a research hotspot in the field of metallurgical industry. The high standard of planar surface quality in the metal manufacturing industry requires that the performance of an automated visual inspection system and its algorithms are constantly improved. This paper attempts to present a comprehensive survey on both two-dimensional and three-dimensional surface defect detection technologies based on reviewing over 160 publications for some typical metal planar material products of steel, aluminum, copper plates and strips. According to the algorithm properties as well as the image features, the existing two-dimensional methodologies are categorized into four groups: statistical, spectral, model, and machine learning-based methods. On the basis of three-dimensional data acquisition, the three-dimensional technologies are divided into stereoscopic vision, photometric stereo, laser scanner, and structured light measurement methods. These classical algorithms and emerging methods are introduced, analyzed, and compared in this review. Finally, the remaining challenges and future research trends of visual defect detection are discussed and forecasted at an abstract level.

Scanning Path Planning for Laser Bending of Metal Tubes

2008 ◽  
Vol 35 (11) ◽  
pp. 1813-1820 ◽  
Author(s):  
王续跃 Wang Xuyue ◽  
陶春华 Tao Chunhua ◽  
许卫星 Xu Weixing ◽  
徐云飞 Xu Yunfei ◽  
吴东江 Wu Dongjiang
Keyword(s):  
Path Planning ◽  
Laser Bending ◽  
Scanning Path ◽  
Scanning Path Planning

scholarly journals Needle path planning and steering in a three-dimensional non-static environment using two-dimensional ultrasound images

2014 ◽  
Vol 33 (10) ◽  
pp. 1361-1374 ◽  
Author(s):  
Gustaaf J. Vrooijink ◽  
Momen Abayazid ◽  
Sachin Patil ◽  
Ron Alterovitz ◽  
Sarthak Misra
Keyword(s):  
Path Planning ◽  
Three Dimensional ◽  
Ultrasound Images ◽  
Two Dimensional ◽  
Needle Path

Hilbert Curve Fractal Stacking in the Application of Path Planning in the Molten Molding

2015 ◽  
Vol 667 ◽  
pp. 82-87
Author(s):  
Zhan Li Wang ◽  
Yan Yan Chao ◽  
Yan Juan Hu
Keyword(s):  
Path Planning ◽  
Fused Deposition Modeling ◽  
Work Piece ◽  
Hilbert Curve ◽  
Processing Efficiency ◽  
Fused Deposition ◽  
Forming Efficiency ◽  
Filling Method ◽  
Scanning Path ◽  
Scanning Path Planning

The scanning process of fused deposition modeling is realizing the fill of certain region, Therefore, reasonable scanning path planning directly affects the forming efficiency and the precision of the work piece. The method of Hilbert curve fractal scanning path which basing on the characteristics of both partition and parallel scanning is put forward basing on the analysis of the existing scanning mode. Application of improved curve filling method for complex curved surface forming planning, according to the characteristics of the Hilbert curve and Hamilton circuit, combined with the characteristics of the scanned level scan path trajectory planning, generate a continuous and comprehensive function value which the weight minimum scanning track under the premise of ensuring the quality of scanning. In order to avoid the generation of island type trajectory, setting a decimal for each loop can easily distinguish between each circuit, finally obtains the scan trajectory. The method can be used to generate scanning track continuous greatly reducing the spray head start and stop times and improves the processing efficiency of the whole, not only to meet the accuracy requirements and can generate non scanning path interference but also high forming efficiency.

scholarly journals Two-Layer Path Planning for Multi-Area Coverage by a Cooperated Ground Vehicle and Drone System

2020 ◽  
Author(s):  
Yangsheng Xia ◽  
Chao Chen ◽  
Jianmai Shi ◽  
Yao Liu ◽  
Guohui Li
Keyword(s):  
Path Planning ◽  
Simulation Experiment ◽  
Feasible Solution ◽  
Programming Model ◽  
Neighborhood Search ◽  
Large Neighborhood Search ◽  
Ground Vehicle ◽  
Random Instances ◽  
Scanning Path

A novel two-layer path planning method for a cooperated ground vehicle (GV) and drone system is investigated, where the GV acts as the mobile platform of the drone and is used to conduct multiple area covering tasks collaboratively. The GV takes the drone to visit a set of discrete areas, while the drone takes off from the GV at potential nodes around each area and scans each area for collecting information. The drone can be recharged in the GV during the time when it travels between different areas. The objective is to optimize the drone’s scanning path for all areas’ coverage and the GV’s travel path for visiting all areas. A 0-1 integer programming model is developed to formulate the problem. A two-stage heuristic based on cost saving strategy is designed to quickly construct a feasible solution, then the Adaptive Large Neighborhood Search (ALNS) algorithm is employed to improve the quality of the solution. A simulation experiment based on the parks in Changsha, China, is presented to illustrate the application of the method. Random instances are designed to further test the performance of the proposed algorithm.

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