ROS and Stereovision Collaborative System

Alaniz-Plata, Ruben; Sergiyenko, Oleg; Flores-Fuentes, Wendy; Tyrsa, Vera; Rodríguez-Quiñonez, Julio C.; Sepulveda-Valdez, Cesar; Andrade-Collazo, Humberto; Mercorelli, Paolo; Линднер, Ларс

doi:10.1007/978-3-031-09791-1_4

Cited by 5 publications

(3 citation statements)

References 47 publications

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“…On the other hand, the authors of the present work have dedicated many years to 3D optical laser rotational scanning systems [3][4][5][6][7][8][9][10][11], and we have confirmed that our laser scanners, by default, naturally decrease their uncertainty, noise, and bias influence, and that their energetic losses and battery lifetime increase when operating in complete darkness. At the same time, in complete darkness, when traditional optical devices based on cameras of any type (APS, CMOS, CCD, omnidirectional fisheye, etc.)…”

Section: Introductionsupporting

confidence: 74%

“…The electronic, mechanical, and design features of the TVS create limitations to the free movement of the elements, restricting the Field of View (FOV). Even though the TVS FOV is not 360 spatial degrees, it is enough to perform spatial measurements with the scanner, as has been widely demonstrated through several research works [3][4][5][6][7]22]. Although this paper analyses the methodology for precise pipeline inspection with our patented TVS [21], any type of robotic mechanism or mobile robot could be adapted to work with our scanning system.…”

Section: Scanning Systemmentioning

confidence: 99%

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Mathematical Modeling for Robot 3D Laser Scanning in Complete Darkness Environments to Advance Pipeline Inspection

Sepulveda-Valdez,

Sergiyenko,

Tyrsa

et al. 2024

Mathematics

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This paper introduces an autonomous robot designed for in-pipe structural health monitoring of oil/gas pipelines. This system employs a 3D Optical Laser Scanning Technical Vision System (TVS) to continuously scan the internal surface of the pipeline. This paper elaborates on the mathematical methodology of 3D laser surface scanning based on dynamic triangulation. This paper presents the mathematical framework governing the combined kinematics of the Mobile Robot (MR) and TVS. It discusses the custom design of the MR, adjusting it to use of robustized mathematics, and incorporating a laser scanner produced using a 3D printer. Both experimental and theoretical approaches are utilized to illustrate the formation of point clouds during surface scanning. This paper details the application of the simple and robust mathematical algorithm RANSAC for the preliminary processing of the measured point clouds. Furthermore, it contributes two distinct and simplified criteria for detecting defects in pipelines, specifically tailored for computer processing. In conclusion, this paper assesses the effectiveness of the proposed mathematical and physical method through experimental tests conducted under varying light conditions.

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Section: Introductionsupporting

confidence: 74%

Section: Scanning Systemmentioning

confidence: 99%

Mathematical Modeling for Robot 3D Laser Scanning in Complete Darkness Environments to Advance Pipeline Inspection

Sepulveda-Valdez,

Sergiyenko,

Tyrsa

et al. 2024

Mathematics

Self Cite

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“…From the perspective of visual perception, ROI is a fairly general term, and the definition is rather diverse depending on the application scenario [ 4 ]. It could represent a variety of pattern classes ranging from natural beings to man-made structures.…”

Section: Introductionmentioning

confidence: 99%

Structured Cluster Detection from Local Feature Learning for Text Region Extraction

Lin

Hsu

2023

Entropy

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The detection of regions of interest is commonly considered as an early stage of information extraction from images. It is used to provide the contents meaningful to human perception for machine vision applications. In this work, a new technique for structured region detection based on the distillation of local image features with clustering analysis is proposed. Different from the existing methods, our approach takes the application-specific reference images for feature learning and extraction. It is able to identify text clusters under the sparsity of feature points derived from the characters. For the localization of structured regions, the cluster with high feature density is calculated and serves as a candidate for region expansion. An iterative adjustment is then performed to enlarge the ROI for complete text coverage. The experiments carried out for text region detection of invoice and banknote demonstrate the effectiveness of the proposed technique.

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Sliding mode observer based fault identification in automatic vision system of robot

Sergiyenko

Tyrsa

Zhirabok

et al. 2023

Control Engineering Practice

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ROS and Stereovision Collaborative System

Cited by 5 publications

References 47 publications

Mathematical Modeling for Robot 3D Laser Scanning in Complete Darkness Environments to Advance Pipeline Inspection

Mathematical Modeling for Robot 3D Laser Scanning in Complete Darkness Environments to Advance Pipeline Inspection

Structured Cluster Detection from Local Feature Learning for Text Region Extraction

Sliding mode observer based fault identification in automatic vision system of robot

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