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12th RSI International Conference on Robotics and Mechatronics, ICRoM 2024

作者： Sedghi, Soheil Tale Masouleh, Mehdi Kalhor, Ahmad School of Electrical and Computer Engineering University of Tehran Human and Robot Interaction Laboratory Tehran Iran

ISBN: (纸本)9798331529734

Parallel robots are versatile but challenging to control due to their complex dynamics and the need for precise modeling. This research presents a novel approach to modular control of parallel robots, utilizing reinforcement learning to dynamically assemble and control complex arbitrary systems. By treating each sub chain of a parallel robot as an individual agent, the proposed method offers a flexible and adaptable framework for various control tasks. The study compares the learning performance of different RL algorithms and proposed decision modeling on the tracking control of a five-bar robot with a 55 cm link length, aiming to achieve an error of less than 5 cm in the PyBullet simulator. In single-agent reinforcement learning, three algorithms (DDPG, PPO, and SAC) were employed, with PPO and SAC effectively solving the problem. In multi-agent reinforcement learning, two algorithms (FACMAC and MAPPO) were utilized. While MAPPO successfully learned the problem, FACMAC exhibited difficulties in grasping the problem. The results obtained from comparing the proposed RL algorithms indicated that single-agent RL learns the control problem better and faster than multi-agent reinforcement learning. In short, the paper focuses on formulating an RL solution which can effectively control parallel robots and can potentially be used for pre-training subchains. © 2024 IEEE.

关键词： Reinforcement learning

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Autonomous Unmanned Aerial Vehicle Indoor Navigation Based on Deep Learning Approaches 11

Autonomous Unmanned Aerial Vehicle Indoor Navigation Based o...

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11th RSI International Conference on Robotics and Mechatronics, ICRoM 2023

作者： Ghasemi, Hamed Balazadeh, Elnaz Malekpour, Shayan Kalhor, Ahmad Masouleh, Mehdi Tale University of Tehran Human and Robot Interaction Laboratory School of Electrical and Computer Engineering Tehran Iran University of Tehran Human and Robot Interaction Laboratory Tehran Iran University of Tehran School of Electrical and Computer Engineering Department of Electrical and Computer Engineering Tehran Iran

ISBN: (纸本)9798350308105

This article presents two approaches based on deep learning for achieving autonomous navigation and subsequently, conducts an in-depth comparative analysis to elaborate their respective performance. Both methods leverage neural networks to facilitate navigation. The first approach employs a deep convolutional neural network to identify suitable areas for forward movement, while the second method utilizes the drone's front camera to capture images, which are then processed by a generative network to generate corresponding depth images. Importantly, both approaches rely solely on an RGB camera, resulting in cost savings for the robot and reduced energy consumption. The training data used for classifying collision-free and appropriate paths were gathered from simulated environments closely resembling real indoor settings. The proposed model calculates the probability associated with each segment of the input image, enabling the selection of the most viable area for drone flight. Incorporating generative networks as a depth estimation module enhances flight accuracy, making navigation in uncharted environments more straightforward. The accuracy of depth estimation was evaluated using standard criteria, achieving an accuracy rate of 84%. This result underscores the effectiveness of the proposed method. © 2023 IEEE.

关键词： Drones

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Switching between MPPT and VSG Controls for Utility-Scale Photovoltaic Plants to Mitigate Power System Oscillations

Switching between MPPT and VSG Controls for Utility-Scale Ph...

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2024 IEEE Energy Conversion Congress and Exposition, ECCE 2024

作者： Ratnakumar, Rajan Venayagamoorthy, Ganesh K. Clemson University Real-Time Power and Intelligent Systems Laboratory Holcombe Department of Electrical and Computer Engineering Clemson United States University of Pretoria Department of Electrical Electronic and Computer Engineering South Africa

ISBN: (纸本)9798350376067

The decline of conventional synchronous generators in the modern power system is driven by the increasing demand for low-inertia/inertia-less renewable energy sources (RES), consequently leading to the growing integration of inverter-based resources (IBRs) into the power system. The incorporation of low-inertia/inertia-less IBRs makes the monitoring and damping of low-frequency electromechanical oscillations (EMOs) crucial. While Virtual Synchronous Generator (VSG) control introduces virtual inertia into the power system, it does not maximize energy capture from RES as effectively as maximum power point tracking (MPPT) does, as it should maintain a power reserve to provide the inertial support and damping. In this study, switching IBRs between MPPT and VSG controls based on an EMO index (EMOI) threshold is proposed to mitigate the emergence of EMO. The impact of the switching control of IBRs is illustrated for a modified two-area, four-machine power system with two large solar photovoltaic plants. Typical results are presented from a simulation on real-time digital simulator (RTDS) to show improved EMOI. © 2024 IEEE.

关键词： Synchronous generators

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Lattice Design for Multiple Topologically Protected Edge Modes 16

Lattice Design for Multiple Topologically Protected Edge Mod...

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16th Pacific Rim Conference on Lasers and Electro-Optics, CLEO-PR 2024

作者： Kim, Gyunghun Suh, Joseph Lee, Dayeong Park, Namkyoo Yu, Sunkyu Seoul National University Intelligent Wave Systems Laboratory Department of Electrical and Computer Engineering Seoul08826 Korea Republic of Seoul National University Photonic Systems Laboratory Department of Electrical and Computer Engineering Seoul08826 Korea Republic of

We propose the lattice design that allows multiple topologically protected edge modes. The scattering between these modes, which is linear, energy preserving, and robust against local disorders, is discussed in terms ...

ISBN: (纸本)9798350372076

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Distributed and networked analysis of volumetric image data for remote collaboration of microscopy image analysis

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Journal of Medical Imaging 2025年第2期12卷 024001页

作者： Chen, Alain Han, Shuo Lee, Soonam Fu, Chichen Yang, Changye Wu, Liming Winfree, Seth Dunn, Kenneth W. Salama, Paul Delp, Edward J. Purdue University School of Electrical and Computer Engineering Video and Image Processing Laboratory West LafayetteIN United States National Institute of Allergy and Infectious Diseases Rocky Mountain Laboratories HamiltonMT United States Indiana University School of Medicine IndianapolisIN United States Purdue University at Indianapolis School of Electrical and Computer Engineering IndianapolisIN United States

Purpose: The advancement of high-content optical microscopy has enabled the acquisition of very large three-dimensional (3D) image datasets. The analysis of these image volumes requires more computational resources than a biologist may have access to in typical desktop or laptop computers. This is especially true if machine learning tools are being used for image analysis. With the increased amount of data analysis and computational complexity, there is a need for a more accessible, easy-to-use, and efficient network-based 3D image processing system. The distributed and networked analysis of volumetric image data (DINAVID) system was developed to enable remote analysis of 3D microscopy images for biologists. Approach: We present an overview of the DINAVID system and compare it to other tools currently available for microscopy image analysis. DINAVID is designed using open-source tools and has two main sub-systems, a computational system for 3D microscopy image processing and analysis and a 3D visualization system. Results: DINAVID is a network-based system with a simple web interface that allows biologists to upload 3D volumes for analysis and visualization. DINAVID enables the image access model of a center hosting image volumes and remote users analyzing those volumes, without the need for remote users to manage any computational resources. Conclusions: The DINAVID system, designed and developed using open-source tools, enables biologists to analyze and visualize 3D microscopy volumes remotely without the need to manage computational resources. DINAVID also provides several image analysis tools, including pre-processing and several segmentation models. © 2025 Society of Photo-Optical Instrumentation Engineers (SPIE).

关键词： Photointerpretation

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Alkali Atomic Density Detection with Arbitrarily Polarized Light

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IEEE Sensors Journal 2025年第11期25卷 20466-20473页

作者： Liu, Xuejing Wang, Menglu Li, Yuhan Wang, Yangtao Zhang, Xuedian Li, Yang University of Shanghai for Science and Technology Key Laboratory of Optical Technology and Instrument for Medicine Ministry of Education School of Optical-Electrical and Computer Engineering Shanghai200093 China University of Shanghai for Science and Technology School of Optical-Electrical and Computer Engineering Shanghai200093 China Tongji University Shanghai Institute of Intelligent Science and Technology Shanghai200093 China

The atomic density of an alkali vapor cell is a critical factor in determining the performance of atomic magnetometers. This paper presents a novel method to detect the density of an alkali atomic ensemble under arbitrary polarization states. By establishing a comprehensive model that correlates the absorption spectrum with the incident light’s polarization, our approach enables real-time and flexible measurements across varying temperatures and polarization angles. Experimental validations are conducted by systematically rotating a quarter-wave plate and controlling the vapor cell temperature, thereby collecting transmission spectra at multiple polarizations. The results demonstrate that the proposed method simplifies density measurements while preserving high accuracy, laying a solid foundation for further research on Spin-Exchange Relaxation-Free (SERF) atomic magnetometers. This technique serves as a versatile and effective tool for in-situ monitoring of alkali metal vapor density in various sensor applications. © 2001-2012 IEEE.

关键词： Absorption spectroscopy

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A Methodology for Estimating Allocation of Electric Vehicle Grid Interfaces in a Distribution System

A Methodology for Estimating Allocation of Electric Vehicle ...

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2024 IEEE PES/IAS PowerAfrica, PowerAfrica 2024

作者： Subasinghe, Imanthi Kalanika Venayagamoorthy, Ganesh K. Real-Time Power and Intelligent Systems Laboratory Holcombe Department of Electrical and Computer Engineering Clemson University Clemson United States Electronic and Computer Engineering University of Pretoria Department of Electrical South Africa

ISBN: (纸本)9798350389388

The integration of electric vehicles (EVs) into the smart grid has introduced new challenges and opportunities for optimizing power and energy management. This paper presents a simple method using a decision-tree to estimate allocation of electric vehicle grid interfaces (EVGIs) for EV charging/discharging, leveraging the nodal capabilities of a distribution system. The future distribution system will cater for vehicle-to-grid (V2G) transactions in addition to grid-to-vehicle (G2V) transactions, thus EVGIs allowing for bidirectional (G2V/V2G) power flows need to be deployed. The proposed decision-tree method is based on nodal power flow ratings and peak demand at the nodes assuming the nodal voltages are maintained within their stability envelopes by volt-var optimization and other voltage control methods. The allocation of EVGIs in the IEEE 34 test node feeder distribution system using the decision-tree method is illustrated. The EVGI allocation using decision-trees is a simple method that can provide insights of a typical distribution system's capability to support EV integration with emerging smart grid technologies. © 2024 IEEE.

关键词： DC distribution systems

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Mutative Evolution for Calculating Maximally Localized Wannier Functions in Photonic Crystals

Mutative Evolution for Calculating Maximally Localized Wanni...

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2024 Conference on Lasers and Electro-Optics/Pacific Rim, CLEO-PR 2024

作者： Lee, Dayeong Lee, Gitae Park, Seungkyun Park, Hyungchul Park, Namkyoo Yu, Sunkyu Intelligent Wave Systems Laboratory Department of Electrical and Computer Engineering Seoul National University Seoul08826 Korea Republic of Photonic Systems Laboratory Department of Electrical and Computer Engineering Seoul National University Seoul08826 Korea Republic of

We propose a neuroevolutionary algorithm to calculate maximally localized Wannier functions in photonic crystals, as an alternative method of conventional gradient-based approaches. © 2024 The Author(s)

关键词： Photonic crystals

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Functionalised B-Cu@F-Ag@Au trimetallic nanomaterials with long term stability for rapid and highly sensitive in situ SERS detection of furfural in transformer oil

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High Voltage 2023年第2期8卷 293-304页

作者： Yu Lei Changding Wang Weiping Kong Mingliang Wang Xinyuan Zhang Abdolmaleki Nima Caisheng Wang Weigen Chen Fu Wan School of Electrical Engineering Chongqing UniversityChongqingChina State Key Laboratory of Power Transmission Equipment and System Security and New Technology Chongqing UniversityChongqingChina Electrical and Computer Engineering Wayne State UniversityWayneNebraskaUSA

The surface-enhanced Raman scattering(SERS)substrates enable a highly sensitive detection of furfural in the transformer ***,detection substrates with long-term stability are still extremely *** this work,we anchored the thiol-containing coupling agents 2,5-dimercapto-1,3,4-thiadiazole(DMTD)and 1,4-benzenedithiol(BDT)on the surface of bubble copper(B-Cu)and flower-like silver nanoparticles(FAg),*** three-dimensional SERS detection substrates with long-term stability by using a combination of chemical reduction and self-assembly methods were *** substrate has a minimum detection limit of 10^(−9) M for rhodamine B in oil with an enhancement factor of up to 2.23×10^(7).Importantly,the three-crystal BCu@F-Ag_(1)@Au_(5) substrate was used for the detection of furfural in the transformer oil with a detection limit of 2 mg/L and a relative standard deviation value of 2.46%.After 60 days of a simulated operation,the detection signal of furfural in the transformer oil samples at 75℃ and still reached the initial value of 77.53%,indicating that the substrate has a good long-term *** triple frame structured SERS detection platform shows great potential in tracking furfural in the aging transformer oil mixing systems.

关键词： stability. stability SERS

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Federated Multi-armed Bandits Under Byzantine Attacks

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2025年第06期6卷 1488-1501页

作者： Saday, Artun Demirel, Ilker Yildirim, Yigit Tekin, Cem Bilkent University Department of Electrical and Electronics Engineering Ankara06800 Turkey Massachusetts Institute of Technology Computer Science and Artificial Intelligence Laboratory CambridgeMA02139 United States

Multi-armed bandits (MAB) is a sequential decision-making model in which the learner controls the trade-off between exploration and exploitation to maximize its cumulative reward. Federated multi-armed bandits (FMAB) is an emerging framework where a cohort of learners with heterogeneous local models play a MAB game and communicate their aggregated feedback to a server to learn a globally optimal arm. Two key hurdles in FMAB are communication-efficient learning and resilience to adversarial attacks. To address these issues, we study the FMAB problem in the presence of Byzantine clients who can send false model updates threatening the learning process. We analyze the sample complexity and the regret of β-optimal arm identification. We borrow tools from robust statistics and propose a median-of-means (MoM)-based online algorithm, Fed-MoM-UCB, to cope with Byzantine clients. In particular, we show that if the Byzantine clients constitute less than half of the cohort, the cumulative regret with respect to β-optimal arms is bounded over time with high probability, showcasing both communication efficiency and Byzantine resilience. We analyze the interplay between the algorithm parameters, a discernibility margin, regret, communication cost, and the arms' suboptimality gaps. We demonstrate Fed-MoM-UCB's effectiveness against the baselines in the presence of Byzantine attacks via experiments. © 2020 IEEE.

关键词： Federated learning

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