3D curvature grinding path planning based on point cloud data

Zhang, Guifang; Wang, Junwei; Cao, Feng; Li, Yuan; Chen, Xiaoqi

doi:10.1109/mesa.2016.7587150

Cited by 15 publications

(4 citation statements)

References 15 publications

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“…Part of the process is presented in Figure 1. The work presented in [9] uses a method that creates a path for 3D grinding using online measurement data of workpieces with complex surfaces. This approach uses a 3D laser scanner and point-cloud data.…”

Section: • Stereo Cameramentioning

confidence: 99%

Data Analysis for Trajectory Generation for a Robot Manipulator Using Data from a 2D Industrial Laser

et al. 2022

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Nowadays, the automation of factory floors is necessary for extensive manufacturing processes to meet the ever-increasing competitiveness of current markets. The technological advances applied to the digital platforms have led many businesses to automate their manufacturing processes, introducing robotic manipulators collaborating with human operators to achieve new productivity, manufacturing quality, and safety levels. However, regardless of the amount of optimization implemented, some quality problems may be introduced in production lines with many products being designed and produced. This project proposes a solution for feature extraction that can be applied to automatic shape- and position-detection using a 2-dimension (2D) industrial laser to extract 3-dimension (3D) data where the movement of the item adds the third dimension through the laser’s beam. The main goal is data acquisition and analysis. This analysis will later lead to the generation of trajectories for a robotic manipulator. The results of this application proved reliable given their small measurement error values of a maximum of 2 mm.

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Section: • Stereo Cameramentioning

confidence: 99%

Data Analysis for Trajectory Generation for a Robot Manipulator Using Data from a 2D Industrial Laser

et al. 2022

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“…The information contained in point clouds can effectively reflect the surface characteristics of a workpiece to be measured, and as such, many researchers process point cloud data directly to achieve robot trajectory planning. Some studies, such as [23][24][25][26], utilize the obtained workpiece point cloud data for path planning to grind the entire workpiece surface. Yang [27] proposed a three-dimensional weld grinding path planning method based on point clouds, and Geng [28] proposed a point-based, cloud-based automatic welding path planning method for steel mesh.…”

Section: Introductionmentioning

confidence: 99%

“…Most trajectory planning methods based on point clouds use plane and point cloud data to slice and obtain the trajectory of the workpiece surface. For example, Ge et al [24] generated grinding paths by creating a series of planes that intersect the target surface, computing intersection lines from point cloud data with the planes, and using local plane fitting to estimate normals at contact points. Zhang et al [26] measured the workpiece surface with a 3D sensor to obtain point cloud data, and obtained the trajectory of the workpiece surface by slicing the preprocessed point cloud data.…”

Section: Introductionmentioning

confidence: 99%

Automatic Aluminum Alloy Surface Grinding Trajectory Planning of Industrial Robot Based on Weld Seam Recognition and Positioning

et al. 2023

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In this paper, we propose a novel method for planning grinding trajectories on curved surfaces to improve the grinding efficiency of large aluminum alloy surfaces with welds and defect areas. Our method consists of three parts. Firstly, we introduce a deficiency positioning method based on a two-dimensional image and three-dimensional point cloud, which enables us to accurately and quickly locate the three-dimensional defective areas. Secondly, we propose a 2D weld positioning method based on the defect area and obtain the spatial position of the 3D weld by combining the relationship between 2D and 3D images. Additionally, we propose an orthogonal projection method from the point cloud to the aluminum alloy surface to calculate the weld reinforcement. Thirdly, we present a space spiral grinding trajectory planning method for complex curved surfaces based on the characteristics of the weld reinforcement, spatial position, and spatial position information of the defect area. This method shortens the grinding time of the defect area and improves efficiency. Simulation and experimental results show that our grinding trajectory planning method is more efficient than other grinding methods in removing defects from the surface of aluminum alloys. Moreover, the defect area after grinding is smoother than before.

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“…In addition to the personalised methods described above, one common method is the point cloud slicing technique [35,36]. This method cuts the workpiece point cloud model through a series of parallel planes.…”

Section: Introductionmentioning

confidence: 99%

Laser Ablation Manipulator Coverage Path Planning Method Based on an Improved Ant Colony Algorithm

Luo

Hou

et al. 2020

Applied Sciences

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Coverage path planning on a complex free-form surface is a representative problem that has been steadily investigated in path planning and automatic control. However, most methods do not consider many optimisation conditions and cannot deal with complex surfaces, closed surfaces, and the intersection of multiple surfaces. In this study, a novel and efficient coverage path-planning method is proposed that considers trajectory optimisation information and uses point cloud data for environmental modelling. First, the point cloud data are denoised and simplified. Then, the path points are converted into the rotation angle of each joint of the manipulator. A mathematical model dedicated to energy consumption, processing time, and path smoothness as optimisation objectives is developed, and an improved ant colony algorithm is used to solve this problem. Two measures are proposed to prevent the algorithm from being trapped in a local optimum, thereby improving the global search ability of the algorithm. The standard test results indicate that the improved algorithm performs better than the ant colony algorithm and the max–min ant system. The numerical simulation results reveal that compared with the point cloud slicing technique, the proposed method can obtain a more efficient path. The laser ablation de-rusting experiment results specify the utility of the proposed approach.

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3D curvature grinding path planning based on point cloud data

Cited by 15 publications

References 15 publications

Data Analysis for Trajectory Generation for a Robot Manipulator Using Data from a 2D Industrial Laser

Data Analysis for Trajectory Generation for a Robot Manipulator Using Data from a 2D Industrial Laser

Automatic Aluminum Alloy Surface Grinding Trajectory Planning of Industrial Robot Based on Weld Seam Recognition and Positioning

Laser Ablation Manipulator Coverage Path Planning Method Based on an Improved Ant Colony Algorithm

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