Optoelectronic Navigation Systems of Autonomous Mobile Ground Robots in Non-deterministic Environment

Sergiyenko, Oleg

doi:10.1007/978-3-031-09791-1_11

Cited by 5 publications

(7 citation statements)

References 47 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…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%

“…MR's actual position becomes the origin of the Coordinate Universal Cartesian System, 1 CCS (of Figure 5), set using the MPU6050 inertial sensor. The pipeline inspection begins with the exploration algorithm, and ensuring MR avoids collisions using the physical dimensions of the inspection system as constraints, this algorithm has been detailly explained in previous works [5,8,20]. Lastly, point cloud segmentation using RANSAC identifies and classifies defects encountered during pipeline inspection (according to Table 1).…”

Section: Xyz Mrmentioning

confidence: 99%

“…The results of this experiment are shown in Figure 10. According to [3,5,8,9], the TVS has a performance improvement under nolight environments. Experiments to demonstrate this were carried out.…”

Section: Measurements Under Different Light Conditionsmentioning

confidence: 99%

See 2 more Smart Citations

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

Sepulveda-Valdez,

Sergiyenko,

Tyrsa

et al. 2024

Mathematics

View full text Add to dashboard Cite

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.

show abstract

Section: Introductionsupporting

confidence: 74%

Section: Xyz Mrmentioning

confidence: 99%

See 1 more Smart Citation

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

Sepulveda-Valdez,

Sergiyenko,

Tyrsa

et al. 2024

Mathematics

View full text Add to dashboard Cite

show abstract

“…In equation (12), if the hue value of each point of captured images, which lies inside the surface model frame S L;in , is similar to the hue value of each point in a model, the fitness value will increase with the voting value of e 1 . These sampling points are represented by dots designated by (A) in Figure 9(b).…”

Section: Definition Of the Fitness Functionmentioning

confidence: 99%

“…9,10 Furthermore, optical laser sensors have been explored for vision tasks in previous studies. [11][12][13][14] However, these sensors often come with a higher cost. With the development of deep-learning technology, monocular RGB images can also achieve pose recognition.…”

Section: Introductionmentioning

confidence: 99%

Expanded photo-model-based stereo vision pose estimation using a shooting distance unknown photo

Tian,

Wang

2024

International Journal of Advanced Robotic Systems

View full text Add to dashboard Cite

Model-based stereo vision pose estimation depends on the establishment of the model. The photo-model-based method simplifies the model-building process with just one photo. Programming languages do not predefine the shapes, colors, and patterns of objects. In the past, however, it was necessary to calculate a pixel per metric ratio, that is, the number of pixels per millimeter of the object, based on the photo’s shooting distance to generate a photo-model with the same size (length and width) as the actual object. It restricts the real application. The proposed method extends the traditional photo-modeling algorithm and relaxes the photo prerequisite for target pose determination. Various pixel per metric ratios will be assumed to generate 3D photo-models of different sizes. These models will then be employed in stereo vision image matching techniques to detect the pose of the target object. Since it is not a data-driven method, it does not require many pictures and pretraining time. This article applies the algorithm to the cleaning of seaports and aquaculture, aiming to locate dead or diseased marine life on the water surface before collection. Pose estimation experiments have been conducted to detect an object’s pose and a prepared photo’s pixel per metric ratio in real application scenarios. The results show that the expanded photo-model stereo vision method can estimate the pose of a target with one pixel per metric ratio unknown photo.

show abstract

Developing a Hardware and Software Complex for Measuring the Three-Dimensional Ice Geometry on Object Surfaces

Zuev,

Dvoynishnikov,

Meledin

et al. 2024

Scanning Technologies for Autonomous Systems

View full text Add to dashboard Cite

Optoelectronic Navigation Systems of Autonomous Mobile Ground Robots in Non-deterministic Environment

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

Expanded photo-model-based stereo vision pose estimation using a shooting distance unknown photo

Developing a Hardware and Software Complex for Measuring the Three-Dimensional Ice Geometry on Object Surfaces

Contact Info

Product

Resources

About