Edge Extraction by Merging the 3D Point Cloud and 2D Image Data

Wang, Ying; Ewert, Daniel; Schilberg, Daniel; Jeschke, Sabina

doi:10.1007/978-3-319-08816-7_61

Cited by 13 publications

(8 citation statements)

References 11 publications

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“…This article uses segment recognition and splicing to complete cable identification and positioning. This method uses a shape matching algorithm to extract a small section of cable features from a plane image, uses point cloud data to calculate the cable center position, and performs feature selection and splicing based on prior conditions [25]- [31]. (1)Feature extraction To solve the problem of background interference, this paper adopts the shape matching method for cable identification.…”

Section: ) Methods Of Recognition and Positioningmentioning

confidence: 99%

Autonomous Live-Line Maintenance Robot for a 10 kV Overhead Line

Feng

Zhang

2021

IEEE Access

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Live work is a dangerous and complex operation that endangers the lives of operators. This paper presents an autonomous live-line maintenance robot (ALMR), which is applied to 10 kV overhead lines. The ALMR can complete most of the operations automatically, requiring only a small amount of correction and operation. The paper briefly introduces the overall design of the ALMR. The main part of the paper describes the work carried out to realize automatic operation: (1) Propose a dynamic hierarchical task planning method that can decompose complex operations into a sequence of instructions that the robot can directly execute and can effectively deal with unexpected situations during operation; (2) solve the problem of recognition and positioning of cables under outdoor sunlight interference and complex backgrounds;(3) realize the robot's motion planning in the live-line scene; (4) build a virtual environment to solve the telepresence problem of remote operation. Field experiments show that the ALMR can replace manual operations such as connecting and disconnecting lead-flow lines, and the operating efficiency is close to that of manual operations.

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Section: ) Methods Of Recognition and Positioningmentioning

confidence: 99%

Autonomous Live-Line Maintenance Robot for a 10 kV Overhead Line

Feng

Zhang

2021

IEEE Access

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“…In the research object of this paper, we mainly focus on features such as workpiece edges and corners. Most of the methods of these feature extraction are based on the defined operators (Weber et al , 2010; Wang et al , 2013; Ni et al , 2016). In addition, Lee and Bo (2016) used the clustering method for edge extraction.…”

Section: Related Workmentioning

confidence: 99%

A robot chamfering system for special-shaped and thin-walled workpieces

et al. 2021

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Purpose This paper aims to propose a robotic automation system for processing special-shaped thin-walled workpieces, which includes a measurement part and a processing part. Design/methodology/approach In the measurement part, to efficiently and accurately realize the three-dimensional camera hand-eye calibration based on a large amount of measurement data, this paper improves the traditional probabilistic method. To solve the problem of time-consuming in the extraction of point cloud features, this paper proposes a point cloud feature extraction method based on seed points. In the processing part, the authors design a new type of chamfering tool. During the process, the robot adopts admittance control to perform compensation according to the feedback of four sensors mounted on the tool. Findings Experiments show that the proposed system can make the tool smoothly fit the chamfered edge during processing and the machined chamfer meets the processing requirements of 0.5 × 0.5 to 0.9 × 0.9 mm2. Practical implications The proposed design and approach can be applied on many types of special-shaped thin-walled parts. This will give a new solution for the automation integration problem in aerospace manufacturing. Originality/value A novel robotic automation system for processing special-shaped thin-walled workpieces is proposed and a new type of chamfering tool is designed. Furthermore, a more accurate probabilistic hand-eye calibration method and a more efficient point cloud extraction method are proposed, which are suitable for this system when comparing with the traditional methods.

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“…There are many mature algorithms to extract the edge, color and geometry information of debris point cloud 20,21 . The methods of feature points and boundary extraction in this study are based on references.…”

Section: A Removal Of Non-relic Debris Points From Laser 3d Scanningmentioning

confidence: 99%

Application of Three-Dimensional Laser Scanning in the Protection of Multi-Dynasty Ceramic Fragments

et al. 2020

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The number of fragments and the variety of primitive cultural relics unearthed in archaeology, especially the mixed fragments of several dynasties unearthed in Qinglong town, Shanghai, pose a great challenge to the manual splicing. The traditional manual comparison method is easy to cause the second damage to the cultural relics. In this paper, the edge feature is extracted based on removing the noise of point cloud, a bilateral filtering point cloud denoising algorithm based on salient features is proposed. By changing the step size and field of view, the Improved Artificial Fish Swarm Algorithm is used to get the matching strategy, and the point cloud is used to reconstruct 3D model by the Dual Quaternion Transformation method. The pairing of fragments and virtual reconstruction can effectively avoid the secondary damage of cultural relic fragments. It provides a feasible artificial intelligence solution for the protection and restoration of similar archaeological excavations.

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Edge Extraction by Merging the 3D Point Cloud and 2D Image Data

Cited by 13 publications

References 11 publications

Autonomous Live-Line Maintenance Robot for a 10 kV Overhead Line

Autonomous Live-Line Maintenance Robot for a 10 kV Overhead Line

A robot chamfering system for special-shaped and thin-walled workpieces

Application of Three-Dimensional Laser Scanning in the Protection of Multi-Dynasty Ceramic Fragments

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