Inspection Mobile Robot’s Control System with Remote IoT-based Data Transmission

Kondratenko, Yuriy; Gerasin, Oleksandr; Kozlov, Oleksiy; Topalov, Andriy; Kilimanov, Bogdan

doi:10.13052/jmm1550-4646.1742

Cited by 10 publications

(5 citation statements)

References 29 publications

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“…To date, various schemes for combining algorithms have been developed and it has been experimentally demonstrated that in some cases a set of basic algorithms is superior in accuracy to the best algorithm presented in this set [14][15][16][17][18]. There are basically two scenarios for combining algorithms [19].…”

Section: Related Workmentioning

confidence: 99%

An Ensemble Approach To Face Recognition In Access Control Systems

Opanasenko,

Fazilov,

Mirzaev

et al. 2024

JMM

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The article proposes a method for recognizing faces in mobile devices, based on an ensemble approach to solving the problem of pattern recognition, which ensures high accuracy of results. According to this approach, the basic algorithm is decomposed into two operators: a recognition operator and a decision rule. The recognition operator calculates estimates of the proximity of the tested object to the given classes. The decision rule, based on these estimates, determines whether the tested object belongs to one of the given classes. The ensemble of recognizing operators is formed in the form of a linear polynomial. The values of the polynomial parameters are calculated based on the solution of the multiparameter optimization problem. Experimental studies were carried out using open databases of facial images. When conducting experiments, it was assumed that two options for using basic algorithms would be implemented: separate and ensemble. The accuracy of recognizing objects in the control sample using an ensemble of recognition operators turned out to be higher compared to the accuracy of the best basic recognition algorithm. The proposed face recognition method can be used in mobile devices, in particular, to verify users when remotely accessing information resources that limited access status.

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Section: Related Workmentioning

confidence: 99%

An Ensemble Approach To Face Recognition In Access Control Systems

Opanasenko,

Fazilov,

Mirzaev

et al. 2024

JMM

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“…Such adaptive robots may be equipped with different tactile sensors and can work separately or may be installed at the moving mothership mobile robot as the second robotic component of MCMC. For mobile robots which can move on inclined, vertical, or ceiling ferromagnetic surfaces (ship hulls, for example), it is very important to ensure high indicators of control and maneuvering characteristics and to provide the required magnetic clamping force between the mobile robot and working surface [ 13 , 15 , 17 , 94 , 95 , 96 , 97 , 98 ]. The mobile robot should track the working surface parameters and create a reliable value of the clamping force for high-reliable MCRC functioning in the action of surface disturbances, taking into account that a ferromagnetic surface may be covered by nonmagnetic layers of dead microorganisms.…”

Section: Related Work and Problem Statementmentioning

confidence: 99%

Machine Learning Techniques for Increasing Efficiency of the Robot’s Sensor and Control Information Processing

Kondratenko

Atamanyuk

Sidenko

et al. 2022

Sensors

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Real-time systems are widely used in industry, including technological process control systems, industrial automation systems, SCADA systems, testing, and measuring equipment, and robotics. The efficiency of executing an intelligent robot’s mission in many cases depends on the properties of the robot’s sensor and control systems in providing the trajectory planning, recognition of the manipulated objects, adaptation of the desired clamping force of the gripper, obstacle avoidance, and so on. This paper provides an analysis of the approaches and methods for real-time sensor and control information processing with the application of machine learning, as well as successful cases of machine learning application in the synthesis of a robot’s sensor and control systems. Among the robotic systems under investigation are (a) adaptive robots with slip displacement sensors and fuzzy logic implementation for sensor data processing, (b) magnetically controlled mobile robots for moving on inclined and ceiling surfaces with neuro-fuzzy observers and neuro controllers, and (c) robots that are functioning in unknown environments with the prediction of the control system state using statistical learning theory. All obtained results concern the main elements of the two-component robotic system with the mobile robot and adaptive manipulation robot on a fixed base for executing complex missions in non-stationary or uncertain conditions. The design and software implementation stage involves the creation of a structural diagram and description of the selected technologies, training a neural network for recognition and classification of geometric objects, and software implementation of control system components. The Swift programming language is used for the control system design and the CreateML framework is used for creating a neural network. Among the main results are: (a) expanding the capabilities of the intelligent control system by increasing the number of classes for recognition from three (cube, cylinder, and sphere) to five (cube, cylinder, sphere, pyramid, and cone); (b) increasing the validation accuracy (to 100%) for recognition of five different classes using CreateML (YOLOv2 architecture); (c) increasing the training accuracy (to 98.02%) and testing accuracy (to 98.0%) for recognition of five different classes using Torch library (ResNet34 architecture) in less time and number of epochs compared with Create ML (YOLOv2 architecture); (d) increasing the training accuracy (to 99.75%) and testing accuracy (to 99.2%) for recognition of five different classes using Torch library (ResNet34 architecture) and fine-tuning technology; and (e) analyzing the effect of dataset size impact on recognition accuracy with ResNet34 architecture and fine-tuning technology. The results can help to choose efficient (a) design approaches for control robotic devices, (b) machine-learning methods for performing pattern recognition and classification, and (c) computer technologies for designing control systems and simulating robotic devices.

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“…• Intelligent polymetric sensor systems are highly efficient as information components of the integrated ships' control systems [7][8][9][10]. • Intelligent automation and robotics systems are exclusive to smart shipyards' production quality and cost efficiency [11][12][13][14][15][16][17][18][19][20].…”

Section: Introductionmentioning

confidence: 99%

Ship Operation Analysis and Optimization via Mobile Application

Zhukov,

Zivenko

2024

JMM

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This paper is devoted to studying the structure and prospects of ship operations analysis and optimization via mobile applications, focusing on integrating multiple existing onboard monitoring and control systems. The main parts of the paper describe the current state of the most essential components of future overall shipping and ship design optimization using onboard and cloud-based monitoring systems from a dual transition point of view. Special attention is paid to the ship’s and its equipment’s efficiency improvements, fuel consumption and emissions reduction, cost-effectiveness enhancement, metrological accuracy, and compliance with current regulations. Timely development and deployment of the proposed onboard monitoring systems, in combination with up-to-date mobile applications and cloud computing, should play a crucial role in promoting sustainable and environmentally friendly shipping practices, improving operational performance, and reducing risks to human life at sea and the environmental impact of shipping. Another objective of this research is to review the current state of infrastructure used for fuel control, focusing on measurement systems and related analytics using appropriate mobile applications. The recommendations for integrating new and adopting existing monitoring systems and equipment for promising alternative fuels must be given to meet current regulations and provide required safety levels and measurement quality.

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Inspection Mobile Robot’s Control System with Remote IoT-based Data Transmission

Cited by 10 publications

References 29 publications

An Ensemble Approach To Face Recognition In Access Control Systems

An Ensemble Approach To Face Recognition In Access Control Systems

Machine Learning Techniques for Increasing Efficiency of the Robot’s Sensor and Control Information Processing

Ship Operation Analysis and Optimization via Mobile Application

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