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International Conference on Unmanned Aircraft systems (ICUAS)

作者： Goran Vasiljević Dean Martinović Stjepan Bogdan Faculty of Electrical Engineering and Computing Laboratory for Robotics and Intelligent Control Systems Unska 3 University of Zagreb Zagreb Croatia

ISBN: (数字)9798331513283

ISBN: (纸本)9798331513290

In this paper, we present a method to control the UAV to follow the power line with a specific position and orientation based only on the measurement of the magnetic field generated by the current flow in the power line. In this way, it is possible to localize the UAV with respect to the power line without the need for additional sensors, even in poor visibility conditions. The measurements from four magnetometers attached to the UAV are used to solve an optimization problem that involves determining the relative pose of the UAV with respect to the power line. Based on the relative pose, the UAV is controlled to follow the power line in a predefined position and orientation. Experiments in a test setup have confirmed that the method is applicable in a realistic environment.

关键词： Location awareness Visualization Power measurement Magnetic field measurement Magnetometers Current measurement Position measurement Autonomous aerial vehicles Magnetic fields Optimization

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Reviewing Fault Diagnosis Methods in Electric Drives: Power Subsystem and Electrical Machine 24

Reviewing Fault Diagnosis Methods in Electric Drives: Power ...

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24th IEEE International Conference of Young Professionals in Electron Devices and Materials, EDM 2023

作者： Demidova, Galina Chen, Hao Li, Yibin Lukichev, Dmitry Anuchin, Alecksey Itmo University Faculty of Control System and Robotics Saint-Petersburg Russia School of Electrical and Power Engineering China University of Mining and Technology Xuzhou China Institute of Marine Science and Technology Shandong University Shandong China Moscow Power Engineering Institute Department of Electric Drives Moscow Russia

ISBN: (纸本)9798350336870

This paper provides a review of popular fault diagnosis methods in the power subsystem and electrical machine of electric drives. The review aims to explore the different approaches used to detect faults in these components and the most common types of faults encountered in electric drives. The paper first provides an overview of the power subsystem and electrical machine and their respective functions within the electric drive system. It then proceeds to discuss the different types of faults that can occur in these components, including overvoltage, undervoltage, overcurrent, and short circuits. The review evaluates the various fault diagnosis methods available for these components, including model-based, signal-based, and artificial intelligence-based approaches. Model-based approaches use mathematical models of the system to detect and diagnose faults. Signal-based approaches rely on the analysis of measured signals to detect changes in system behavior that indicate a fault. Artificial intelligence-based approaches use machine learning algorithms to identify patterns in data and detect faults. Model-based approaches are highly accurate but can be computationally intensive. Signal-based approaches are less computationally intensive but may be less accurate in certain situations. Artificial intelligence-based approaches are versatile but require significant amounts of data for training. This review provides a comprehensive overview of the current state-of-the-art in fault diagnosis methods for the power subsystem and electrical machine of electric drives. The review concludes by suggesting potential areas for future research to further improve the accuracy and efficiency of fault diagnosis methods for electric drives. © 2023 IEEE.

关键词： Failure analysis

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control Aspects in Programming by Demonstation for Robotic Deep- Micro- Hole Drilling

Control Aspects in Programming by Demonstation for Robotic D...

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Mediterranean Conference on control and Automation (MED)

作者： Bruno Maric Frano Petric Matko Orsag LARICS Laboratory for Robotics and Intelligent Control Systems Faculty of Electrical Engineering and Computing University of Zagreb Zagreb Croatia

ISBN: (数字)9798350395440

ISBN: (纸本)9798350395457

This paper explores control aspects in a collab-orative robotic system designed to replicate human operators' drilling skills in deep- micro- hole tasks, focusing on the glass-container mould industry. To replicate human performance, we develop a single-DOF Impedance-based drill controller for a standard industrial position-controlled robot, enhancing safe and smooth interactions between the drill bit and the mould. To address high feed rates observed in worker demonstrations and prevent bit breaks, we focus on minimizing non-axial motion during drilling on an off-the-shelf available industrial manipulator KUKA KR 10. This involves analyzing the impact of joint dynamics on drill motion and designing a control system for the robot's low-level control to achieve axial drill motion. We show that the proposed joint control system that takes into account relationship between joint and tool dynamics outperforms available robot low-level control in minimizing non-axial motion, leading to the robot being able to outperform the human in deep- micro- hole drilling.

关键词： Drilling Service robots Dynamics Robot control Time factors Synchronization Task analysis

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AI-Enhanced Structural Health Monitoring with a Multi-Rotor Aerial Vehicle

AI-Enhanced Structural Health Monitoring with a Multi-Rotor ...

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International Conference on Unmanned Aircraft systems (ICUAS)

作者： Filip Zorić Ana Milas Tamara Petrović Zdenko Kovačić Matko Orsag Faculty of Electrical Engineering and Computing LARICS Laboratory for Robotics and Intelligent Control Systems University of Zagreb Zagreb Croatia

ISBN: (数字)9798350357882

ISBN: (纸本)9798350357899

Roads, bridges, tunnels, railways and canals are crucial for the transportation of goods and people in modern society. Modern infrastructure is subject to damage and requires therefore regular inspection and maintenance to remain safe and functional. While this can be done manually, large parts of the mentioned infrastructure are hardly accessible, which is a main motivational factor for the use of multi-rotor aerial vehicles (MAV s) for inspection and maintenance tasks. MAV s, paired with novel deep learning computer vision techniques, such as instance segmentation, are emerging as an obvious choice for automating certain parts of structural health monitoring (SHM). In this manuscript, we provide an overview of available SHM datasets and how they can be utilized for the task of autonomous crack detection. We use available datasets to train and compare two neural network architectures for instance segmentation. The segmented crack instances are then localized in a global coordinate frame to perform autonomous mapping of the potentially dangerous infrastructure defects. Experimental studies demonstrate the effectiveness of the proposed SHM approach, which results in precisely localized infrastructure defects marked on the global map.

关键词： Instance segmentation Irrigation Structural panels Neural networks Transportation Inspection Rail transportation

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Adaptive parameter estimation of linear time invariant generators in finite time with relaxed excitation conditions

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IFAC-PapersOnLine 2022年第12期55卷 97-102页

作者： Nguyen K. Tung Mikhail M. Yachmenkov Sergey M. Vlasov Anton A. Pyrkin Department of Control Systems and Robotics ITMO University Kronversky Pr. 49 St. Petersburg 197101 Russia

The problem of identifying the constant parameters of LTI generators in finite time are considered. The signal is represented as the output of a linear generator, the parameters of the state matrix and initial conditions are unknown. The main idea is to parameterize the signal using delays and obtain a linear or nonlinear regression model. The performance of the algorithms considered in the article is illustrated by computer modeling.

关键词： identification Jordan form matrix linear regression model generator

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The Development of the Cutting Tools and Toolholders Parameters Unified Database

The Development of the Cutting Tools and Toolholders Paramet...

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International Russian Automation Conference (RusAutoCon)

作者： Tatiana V. Basova Yuri S. Andreev Maria V. Basova Faculty of Control Systems and Robotics ITMO University St. Petersburg Russia Faculty of Arms and Weapons Systems Baltic State Technical University «VOENMEH» Named After D.F. Ustinov St. Petersburg Russia

This paper deals with the consideration of the cutting tools and toolholders information data processing issues caused by the different representation of these tools by their manufacturers and users. This problem complicates the interactions between various software systems, thereby increasing the time required for technological production preparation. As a prospective solution to these problems, the cutting tools and toolholders parameters unified database (DB) has been developed. The proposed DB includes the necessary information for performing the key tasks in the technological production preparation regarding cutting tools and toolholders. The developed DB is based on the international standard ISO 13399 and the GTC (Generic Tool Catalog) format, as well as additional tool description parameters required to satisfy the production needs. Therefore, this research aims to improve the processes of technological production preparation and ensure the products manufacturing efficiency.

关键词：

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A New ECG Signal Processing Method Based on Wide-Band Notch Filter

A New ECG Signal Processing Method Based on Wide-Band Notch ...

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2020 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering, EIConRus 2020

作者： Altay, Yeldos A. Kremlev, Artem S. Zimenko, Konstantin A. ITMO University Faculty Control Systems and Robotics Saint Petersburg Russia

ISBN: (纸本)9781728157610

This article presents the task of ECG signal processing a wide-band notch filter. It is proposed to use a cascade wide-band notch filter. The proposed method allows us to increase the accuracy of ECG signal processing and reduce wide-band electrical noise. The effectiveness proposed method for ECG signal processing by experimental results is considered. © 2020 IEEE.

关键词： Notch filters

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The Journey/DAO/TAO of Embodied Intelligence: From Large Models to Foundation Intelligence and Parallel Intelligence

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IEEE/CAA Journal of Automatica Sinica 2024年第6期11卷 1313-1316页

作者： Tianyu Shen Jinlin Sun Shihan Kong Yutong Wang Juanjuan Li Xuan Li Fei-Yue Wang College of Information Science and Technology Beijing University of Chemical TechnologyBeijing 100029China School of Electrical and Information Engineering Jiangsu UniversityZhenjiang 212013China State Key Laboratory for Turbulence and Complex Systems Department of Advanced Manufacturing and RoboticsCollege of EngineeringPeking UniversityBeijing 100871China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China Peng Cheng Laboratory Shenzhen 518000China State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190 Faculty of Innovation Engineering Macao University of Science and TechnologyMacao 999078China IEEE

THE tremendous impact of large models represented by ChatGPT[1]-[3]makes it necessary to con-sider the practical applications of such models[4].However,for an artificial intelligence(AI)to truly evolve,it needs to possess a physical“body”to transition from the virtual world to the real world and evolve through interaction with the real *** this context,“embodied intelligence”has sparked a new wave of research and technology,leading AI beyond the digital realm into a new paradigm that can actively act and perceive in a physical environment through tangible entities such as robots and automated devices[5].

关键词： Intelligence DAO TAO

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Machine Learning in Predicting the Impact of Filter Parameters on the Accuracy of Biosignal Measurement

Machine Learning in Predicting the Impact of Filter Paramete...

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Digital Signal Processing and its Applications (DSPA), International Conference on

作者： Yeldos A. Altay Raisa K. Uskenbayeva Abu-Alim E. Ayazbay Alexey V. Fedorov Department of Robotics and Technical Means of Automation Satbayev University Almaty Kazakhstan Institute of Automation and Information Technologies Vice-Rector Satbayev University Almaty Kazakhstan Electronic engineering Almaty University of Power Engineering and Telecomunications Almaty Kazakhstan Faculty of Control Systems and Robotics ITMO University Saint-Petersburg Russian Federation

ISBN: (数字)9798331518752

ISBN: (纸本)9798331518769

In this scientific article under consideration, a machine learning model has been developed that allows predicting the impact of filter parameters on the accuracy of measuring a biosignal - an ECG (electrocardiography) signal. For the first time, quantitative results have shown the degree of influence and the error introduced into the measured biosignal and described through dependence. The results of assessing the obtained relationship of indicators demonstrate an inverse correlation relationship that characterizes a decrease in the accuracy of measurement at the output of a high-order digital filtering system. The machine learning model is based on the linear regression method the dependence of which is approximated by the method based on least squares and visualized using a scattergram. The adequacy of the developed machine learning model was confirmed by calculating the coefficient of determination and checking its statistical significance. The developed model can be used to create new or improve existing biomedical data processing systems to increase the reliability of the results.

关键词： Accuracy Shape Filtering Biological system modeling Machine learning Biomedical measurement Electrocardiography Distortion Distortion measurement Digital filters

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Automated Suckering of Vines with a Mobile Robot and a Torque-controlled Suckering Tool 5

Automated Suckering of Vines with a Mobile Robot and a Torqu...

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5th IEEE International Conference on Smart systems and Technologies, SST 2022

作者： Stuhne, Dario Vatavuk, Ivo Hrabar, Ivan Vasiljević, Goran Kovačić, Zdenko University of Zagreb Faculty of EE&C Zagreb Croatia University of Zagreb LARICS Laboratory for Robotics and Intelligent Control Systems Faculty of Electrical Engineering and Computing Zagreb10000 Croatia

ISBN: (数字)9781665482158

ISBN: (纸本)9781665482158

The research presented in this paper focuses on the development of fully automated and autonomous vine suckering, a seasonal viticulture activity required to remove all unwanted shoots from the vine trunks. This requires human workers to do a lot of strenuous work, often using only their hands or tools such as clippers or shears. The suckering is done during the early growing season (usually April-May) to provide more energy, water, and nutrients to the main shoots. Commercially available suckering machines appear to be a large-scale solution. However, their performance varies between 10% and 85% and their purely mechanical nature can easily cause damage to the vines. In this paper, we present a concept for autonomous suckering using a mobile robot equipped with a special suckering tool driven by a torque-controlled DC motor that protects the vine from damage. The proposed suckering system was designed, analysed and experimentally validated in a real vineyard. The results showed that the system was able to remove about two thirds of the unwanted shoots, reaching a suckering rate of more than 86 vines per hour. © 2022 IEEE.

关键词： Mobile robots

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