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检索条件"机构=Department of Robotics and Control Engineering"

共 1741 条记录，以下是291-300 订阅

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Simulated Scattering of a Beam Carrying Orbital Angular Momentum from a Microparticle

Simulated Scattering of a Beam Carrying Orbital Angular Mome...

引用

2023 Conference on Lasers and Electro-Optics, CLEO 2023

作者： McCarthy, John E. Avramov-Zamurovic, Svetlana Hart, Matthew B. Sivaprakasam, Vasanthi Weapons Robotics and Control Engineering Department United States Naval Academy 597McNair Rd AnnapolisMD21401 United States Optical Sciences Division United States Naval Research Laboratory 597McNair Rd AnnapolisMD21401 United States

ISBN: (纸本)9781957171258

We use multiphysics software COMSOL to simulate and evaluate interactions between structured light carrying orbital angular momentum and a single microparticles. We investigate the impact of particle location with respect to the structured light spatial intensity distribution. © Optica Publishing Group 2023 © 2023 The Author(s)

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Interaction of a Beam Carrying Orbital Angular Momentum with an Ice Microparticle

Interaction of a Beam Carrying Orbital Angular Momentum with...

引用

2023 Propagation Through and Characterization of Atmospheric and Oceanic Phenomena, pcAOP 2023 in Optica Imaging Congress - Part of Imaging and Applied Optics Congress 2023

作者： Avramov-Zamurovic, Svetlana McCarthy, John E. Hart, Matthew B. Sivaprakasam, Vasanthi Weapons Robotics and Control Engineering Department United States Naval Academy 597 McNair Rd AnnapolisMD21401 United States Optical Sciences Division United States Naval Research Laboratory 4555 Overlook Ave. SW WashingtonDC20375 United States

We investigate the interaction of light carrying orbital angular momentum and a single ice microparticle using COMSOL multiphysics software. We report on the intensity and phase spatial distribution within the observa... 详细信息

ISBN: (纸本)9781957171289

关键词： Gaussian beams Light beams Light propagation Mueller matrices Orbital angular momentum multiplexing Structured light

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Enhancing the Performance of Machine Learning Classification Models

Enhancing the Performance of Machine Learning Classification...

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International Symposium on INFOTEH-JAHORINA (INFOTEH)

作者： Cihat Talat Akpinar Özcan Koşar Akif Durdu Computer Engineering Research and Development Elfatek Elektronik Ltd. Co. Konya Turkey Department of Electrical and Electronics Engineering Robotics Automation Control Laboratory (RAC-LAB) Konya Technical University Konya Turkey

ISBN: (数字)9798331515799

ISBN: (纸本)9798331515805

This study aims to compare and improve the performance of four different machine learning algorithms (Naive Bayes, Multi-Layer Perceptron (MLP), Decision Trees, and Support Vector Machines (SVM)) in classification problems. The analyses emphasize the impact of data preprocessing steps and hyperparameter optimization on model performance. As part of the data preprocessing, missing values were imputed, categorical data were transformed into numerical data, and normalization procedures were applied. It was observed that normalization significantly enhanced the performance of the MLP and SVM algorithms in particular. Furthermore, additional improvements in accuracy rates were achieved through hyperparameter optimization. Naive Bayes and Decision Trees were found to exhibit stable performance regardless of data scaling. This study demonstrates that proper data preprocessing and model selection can significantly enhance algorithm performance in classification problems.

关键词： Support vector machines Accuracy Machine learning algorithms Data preprocessing Hyperparameter optimization Data models Bayes methods Classification algorithms Numerical models Decision trees

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Virtual Reality Solutions for Troubleshooting Autonomous Industrial Mobile Robots

Virtual Reality Solutions for Troubleshooting Autonomous Ind...

引用

International Symposium on INFOTEH-JAHORINA (INFOTEH)

ISBN: (数字)9798331515799

ISBN: (纸本)9798331515805

This study aims to develop a virtual reality (VR) application to improve the fault detection and troubleshooting processes of autonomous industrial mobile robots. The complex systems and operating environments of autonomous robots make fault detection challenging for users, requiring effective and user-friendly solutions to overcome these difficulties. In this context, the Robot Operating System (ROS) was utilized to detect errors in robots and record these errors in a database. Thanks to the modular structure and robust communication infrastructure offered by ROS, faults in the robots were monitored and analyzed through ROS *** study demonstrates the effective use of VR technology in the maintenance and repair processes of autonomous industrial mobile robots. By integrating ROS-based data collection and fault detection into a VR environment for user training, robot operators are enabled to troubleshoot faults more quickly and effectively. In this way, it is aimed to achieve time and cost savings in industrial processes.

关键词： Training Service robots Databases Fault detection Operating systems Virtual reality Maintenance engineering Maintenance Mobile robots Monitoring

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Optimizing Parameters for Hybrid DNN-UKF State Estimation in Autonomous Air Refueling

Optimizing Parameters for Hybrid DNN-UKF State Estimation in...

引用

International Conference on Unmanned Aircraft Systems (ICUAS)

作者： Leo Wagner James Andersen Donald H. Costello Violet Mwaffo Weapons Robotics and Control Engineering Department United States Naval Academy Annapolis Maryland United States MATRIX Lab A. James Clark School of Engineering University of Maryland College Park MD United States

ISBN: (数字)9798331513283

ISBN: (纸本)9798331513290

The future of the United States Navy's (USN) carrier airwing hinges on effective Uncrewed Aerial Vehicles (UAVs), whose autonomy critically depends on robust aerial refueling systems. This work seeks to refine the process and measurement noise parameters in a hybrid Deep Neural Network (DNN) and Kalman Filter (KF) framework to improve drogue tracking reliability under challenging operational conditions. The proposed study employs a structured experimentation protocol combining simulated lab environments-featuring robotic arms replicating drogue motions-along with video datasets from actual refueling operations. Preliminary results obtained via a trial-and-error tuning approach indicate promising performance, achieving an overall RMSE of 0.155 m. Building on these encouraging findings, we seek to implement systematic fine tuning methods, specifically grid search and Bayesian optimization, to further reduce RMSE and enhance system accuracy and robustness. The ultimate goal is to advance the operational readiness of autonomous aerial refueling, laying the groundwork for the next generation of USN carrier-based aviation.

关键词： Systematics Tracking Noise Artificial neural networks Robustness Bayes methods Calibration State estimation Tuning Optimization

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TinyML Speech Classification Embedded Ai Module for Hand Rehabilitation Device

TinyML Speech Classification Embedded Ai Module for Hand Reh...

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Mechatronics, control and robotics (ICMCR), International Conference on

作者： Arkorn Numsomran Arjin Numsomran Jutarut Chaoraingern Triam Udom Suksa Pattanakarn Suvarnabhumi School Bangkok Thailand Department of Instrumentation and Control Engineering School of Engineering King Mongkut's Institute of Technology Ladkrabang Bangkok Thailand Department of Robotics and AI Engineering School of Engineering King Mongkut's Institute of Technology Ladkrabang Bangkok Thailand

ISBN: (数字)9798331544546

ISBN: (纸本)9798331544553

Recent advancements in artificial intelligence and machine learning have significantly improved healthcare, especially in the development of assistive technologies for rehabilitation. This paper introduces a method for hand rehabilitation that utilizes the capabilities of tiny machine learning to enhance speech classification in a rehabilitation device. The proposed method employs a CNN model capable of classifying speech signals that are indicative of different hand movement patterns. Patients emit these speech signals during prescribed hand exercises, which are crucial for their rehabilitation process. The main focus of this study is on training and deploying a speech classification system that can work in the resource-limited environment of TinyML platforms. We detail the process of capturing speech data, preprocessing it, and extracting the most features relevant to different hand movements. Our results show that using TinyML to help with hand rehabilitation works. The method we came up with shows how TinyML could change the way rehabilitative devices are controlled, and it also shows us what personalized and easy-to-use rehabilitation tools might look like in the future.

关键词： Hands Training Technological innovation Tiny machine learning Medical treatment Speech recognition Transforms Speech enhancement Feature extraction Robots

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An Improved Magnetic Field SLAM Algorithm Based on Iterative Extended Kalman Filter and Gaussian Process Regression

An Improved Magnetic Field SLAM Algorithm Based on Iterative...

引用

International Conference on control, Automation, robotics and Vision (ICARCV)

作者： Adeb Magad Muhammad Mysorewala Department of Control and Instrumentation Engineering King Fahad University of Petroleum and Minerals Dhahran Saudi Arabia Department of Control and Instrumentation Engineering Interdisciplinary Research Center for Smart Mobility and Logistics Interdisciplinary Research Center for Intelligent Manufacturing and Robotics King Fahad University of Petroleum and Minerals Dhahran Saudi Arabia

ISBN: (数字)9798331518493

ISBN: (纸本)9798331518509

This paper introduces an approach for magnetic field simultaneous localization and mapping by leveraging Reduced-Rank Gaussian Process Regression. The proposed algorithm aims to improve the efficiency and accuracy of magnetic field-based localization in environments with spatial variations. The methodology involves representing the magnetic field potential as a sum of basis functions. The use of Reduced-Rank Gaussian Process Regression facilitates a streamlined representation, enabling faster computation and reduced storage requirements. Then, two estimation methods are designed: an Extended Kalman Filter and Iterative Extended Kalman Filter methods to estimate the states of the dynamic model. Simulation results have demonstrated the effectiveness of the proposed approaches in estimating the true dynamic states, with slight improvement of the Iterative Extended Kalman Filter accuracy at certain magnetic field length scales, compared to the Extended Kalman Filter design.

关键词： Location awareness Simultaneous localization and mapping Accuracy Simulation Magnetic separation Gaussian processes Aerodynamics Iterative algorithms Kalman filters Robots

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Event- Triggered based control of Robotic Arm under Denial of Service 21

Event- Triggered based Control of Robotic Arm under Denial o...

引用

21st International Multi-Conference on Systems, Signals and Devices, SSD 2024

作者： Abubakar, Abdulrazaq Nafiu Yahaya, Jamilu Umar Ma'Aruf, Muhammad Mysorewala, Muhammad Faizan Saif, Abdul-Wahid A. King Fahd University of Petroleum and Minerals Control and Instrumentation Engineering Department Dhahran31261 Saudi Arabia Interdisciplinary Research Center for Smart Mobility and Logistics King Fahd University of Petroleum and Minerals Dhahran31261 Saudi Arabia Interdisciplinary Research Center for Intelligent Manufacturing and Robotics King Fahd University of Petroleum and Minerals Dhahran31261 Saudi Arabia

ISBN: (纸本)9798350374131

In this paper, we studied the finite-time stability of robotic arm systems against Denial of Service attacks, when the link between the plant and the controller is often interrupted. In order to do this, a method is suggested that relies on an event-triggered mechanism which is based on the rate of change of the Lyapunov function, that keeps the system finite-time stable while simultaneously reducing the quantity of data interchange in the network. The suggested event-triggered finite-time controller's vulnerability to Denial of Service attacks is then assessed, and sufficient limitations on the length of a Denial of Service are identified to ensure the system's stability within a specified time frame. Lastly, a simulation study is used to show how effective the suggested strategy is. © 2024 IEEE.

关键词： System stability

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Case Study of Supplementary PMSM for Low-Speed Wind Turbine 18

Case Study of Supplementary PMSM for Low-Speed Wind Turbine

引用

18th International Scientific Technical Conference Alternating Current Electric Drives, ACED 2021

作者： Poliakov, Nikolai Vorobev, Konstantin Demidova, Galina Rassolkin, Anton Ramensky, Dmitry Faculty of Control System and Robotics ITMO University Saint Petersburg Russia Tallinn University of Technology Department of Electrical Power Engineering and Mechatronics Tallinn Estonia Zubax Robotics Tallinn Estonia

ISBN: (纸本)9781665412483

In the last decades, the renewables market is focused on distributed grids and solutions suitable for private use in households. A low-speed wind turbine based on the Magnus effect is one of the promising technologies in that area. By its construction, for the power management, Magnus effect-based wind turbine requires additional motors to control the rotational speed of the blades. An integrated motor-drive system for Unmanned Autonomous Vehicles (UAVs) matching the requirements in terms of weight, size, rotational speed, and controllability. In this case study, an application of the permanent magnet synchronous motor (PMSM) designed for UAVs in a Magnus effect-based wind turbine prototype is presented. The control system design methodology is presented, and the performance of the system is experimentally evaluated. © 2021 IEEE.

关键词： Wind turbines

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Finite Element Method Based Toolchain for Simulation of Proximity Estimation Using Electronic Skin 10th

Finite Element Method Based Toolchain for Simulation of Pr...

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Proceedings of the 10th Machine Intelligence and Digital Interaction Conference, MIDI 2022

作者： Ostaszewska-Liżewska, Anna Klimaszewski, Jan Department of Mechatronics Institute of Metrology and Biomedical Engineering Warsaw Univeristy of Technology ul. Sw. A. Boboli 8 Warsaw02-525 Poland Department of Mechatronics Institute of Automatic Control and Robotics Warsaw Univeristy of Technology ul. Sw. A. Boboli 8 Warsaw02-525 Poland

ISBN: (纸本)9783031376481

The emergence of new areas of human-robot cooperation creates the need to ensure human safety in this regard. Therefore, there is a need to develop new sensors to detect the presence of a human in the vicinity of a robot. One such sensor is an electronic skin (e-skin). Manufacturing and testing new e-skin prototypes is labor-intensive. This paper presents a software toolchain developed to simulate the operation of an e-skin used to detect human proximity. The toolchain is based on the finite element method and has been developed exclusively with free and open-source software. The presented toolchain makes it possible to test e-skin modifications without the need for a physical prototype and significantly reduces implementation costs. The developed solution is multi-platform and allows parallel and multi-threaded calculations conducted on multiple machines simultaneously. This paper presents modeling results obtained for a simplified e-skin sensor, which are consistent with experimental results on the actual model. © 2023, The Author(s).

关键词： Finite element method

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