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International Conference on Renewable Energy Research and Applications (ICRERA)

作者： Kazuki Abe Yoshiki Sasaki Hiroshi Takami Fuminori Ishibashi Koji Shibasaki Maruwa Takumi Ebara Graduate School of Electrical Eng. and Computer Science Shibaura Institute of Technology Koto-ku Tokyo Japan Dept. of Electrical Eng. and Robotics Course College of Engineering Shibaura Institute of Technology Koto-ku Tokyo Japan Dept. of Electrical Eng. Faculty of Engineering Shibaura Institute of Technology Koto-ku Tokyo Japan Electronic Inc. Kashiwa-shi Chiba Japan Maruwa Electronic Inc. Kashiwa-shi Chiba Japan

ISBN: (数字)9798350375589

ISBN: (纸本)9798350375596

This paper describes analysis and evaluation of harmonics reduction for Active LC Low Pass Filter (LC-LPF) attached Surface Permanent Magnet Synchronous Motor (SPMSM) drive operated by IRM-ILQ (Inverse Reference Model - Inverse Linear Quadratic) current control. Harmonics due to high-speed switching of inverter should be reduced since it brings not only low efficiency motor drive such as torque ripple, also cause electromagnetic interference (EMI) problems. Those problems will be solved by appending LC-LPF though, LC resonant phenomena against inverter's carrier frequency and motor's operating frequency should be considered. The IRM-ILQ control is classified into modern control methods and simultaneously transacts multiple variables. Owing to it, stable motor drive can be realized even though LC-LPF is attached. In experiments, degrees of the harmonics reduction by Active LC-LPF are evaluated via Fast Fourier Transform (FFT) analysis and Total Harmonic Distortion (THD) and confirmed 2 % of voltage distortion on average in rated speed region.

关键词： Current control Motor drives Total harmonic distortion Fast Fourier transforms Electromagnetic interference Switches Harmonic analysis Distortion Voltage control Power harmonic filters

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Centrifugal Microfluidic Based Painless Blood Sample Collection for Hematocrit Measurement

Centrifugal Microfluidic Based Painless Blood Sample Collect...

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Biomedical Engineering International Conference (BMEiCON)

作者： Santi Rattanavarin Thanapat Sangkharat Ekachai Juntasaro Witsaroot Sripumkhai Pattaraluck Pattamang Norabadee Ranron Numfon Khemthongcharoen Chompunoot Sinthupibulyakit Chamras Promptmas Chayapitcha Saesue Jiraskul Udarwudhipong Wutthinan Jeamsaksiri Department of Production and Robotics Engineering Faculty of Engineering King Mongkut’s University of Technology North Bangkok (KMUTNB) Bangkok Thailand Mechanical Engineering Simulation and Design Group (MESD) Sirindhorn International Thai-German Graduate School of Engineering (TGGS) King Mongkut’s University of Technology North Bangkok (KMUTNB) Bangkok Thailand Thai Microelectronics Center (TMEC) National Electronics and Computer Technology Center (NECTEC) National Science and Technology Development Agency (NSTDA) Chachoengsao Thailand Infrastructure Development Division (IDD) National Science and Technology Development Agency (NSTDA) Pathum Thani Thailand National Electronics and Computer Technology Center (NECTEC) National Science and Technology Development Agency (NSTDA) Pathum Thani Thailand Faculty of Medical Technology Huachiew Chalermprakiet University Samut Prakan Thailand Department of Biomedical Engineering Faculty of Engineering Mahidol University Nakhon Pathom Thailand

This work demonstrates a centrifugal microfluidic chip design for painless blood collection and hematocrit measurement. The fluid channel in the microfluidic chip was fabricated using a laser-cutting method. An optimal dimension of the negative pressure chamber was designed to control the maximum sample volume obtained for further hematocrit examination. The estimated blood sample of 20 µl could be obtained based on the negative pressure driven by finger press actuation on the negative pressure chamber of the microfluidic chip. The repeatability of blood volume collection evaluated by a laboratory technician was 21.126±0.001 µl with a coefficient of variation (CV) of 5.32%. The sample volume used in this centrifugal microfluidic chip was around three times lower than that used in the standard method. Pack red cell preparation for hematocrit examination in the microfluidic chip could be achieved using a centrifugation speed around 2.4 times lower than that used in the standard method. The hematocrit examination by our centrifugal microfluidic chip and the standard method was 41.75±0.77 (1.84 %CV), and 41.5±0.71 (1.7 %CV), respectively. The results showed that the hematocrit measurements in our centrifugal microfluidic chip were compatible with those measured by the standard method.

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New High Boost DC-DC Converter for Renewable Energy Conversion

New High Boost DC-DC Converter for Renewable Energy Conversi...

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International Conference on Communications and Electronics, ICCE

作者： Dinh-Tuyen Nguyen Truong-Khang Duong Truong-Duy Duong Trong-Nha Quang Ton Duc Do Faculty of Electrical and Electronics Engineering Ho Chi Minh City University of TechnologyVNU-HCM Ho Chi Minh City Vietnam Dept. Electrical and Computer Engineering Wayne State University Detroit MI USA High Volume Power Design Advanced Energy Industries Inc Eden Prairie MN USA Dept. Robotics and Mechatronics School of Science and Technology Nazarbayev University Kazakhstan

ISBN: (数字)9798350379792

ISBN: (纸本)9798350379808

This paper proposes a high-boost power converter for renewable energy systems. The suggested converter exhibits a simplified structure by replacing a diode in the switched-inductor cell with an active power switch to reduce the total voltage stress on the semiconductor device, get cost reduction, and improve efficiency. Additionally, the common ground feature inherent in the introduced topology expands its potential for renewable energy applications. Finally, the simulation verifications are performed using PSIM software to confirm the effectiveness of the suggested approach, and a detailed comparison study between the basic switched-inductor converter and the suggested converter is also presented.

关键词： Renewable energy sources Costs Simulation Prototypes Voltage Switches Software

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SPEECH and TREMOR TESTER - MONITORING of NEURODEGENERATIVE DISEASES USING SMARTPHONE technology

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Diagnostyka 2020年第2期21卷 31-39页

作者： Chronowski, Maurycy Klaczyński, Maciej Dec-Ćwiek, Malgorzata Porębska, Karolina Sawczyńska, Katarzyna AGH University of Science and Technology Faculty of Mechanical Engineering and Robotics Adama Mickiewicza 30 Kraków30-059 Poland Department of Neurology Jagiellonian University Collegium Medicum Botaniczna 3 Kraków31-503 Poland

One of the most frequently diagnosed neurodegenerative disorders, along with Alzheimer’s disease, is Parkinson’s disease. It is a slowly progressing disease of the central nervous system that affects parts of the brain which are responsible for one’s motor functions. Despite the frequency of its occurrence among the elderly population, there has not yet been established a universal approach towards its certain diagnostics ante mortem. The study presents a pilot experiment regarding the assessment of the usefulness of simultaneous processing and analysis of speech signal and hand tremor accelerations for patient’s screening and monitoring of the progress in healing, using the data acquired with a mid-range Android smartphone. During the study, a mobile device of this kind was used to record the patients of the Department of Neurology, University Hospital of the Jagiellonian University in Kraków and a control group of healthy persons over the age of 50. The samples were then analysed and an attempt towards classification was made using statistical methods and machine learning techniques (PCA, SVM, LDA). It was shown that even for a limited population, the classifier reaches about 85% accuracy. Another topic discussed in the study is the possibility of implementing a fully automated mobile system for the monitoring of the disease’s progression. Propositions of further research were also drawn. © 2020 Polish Society of Technical Diagnostics. All rights reserved.

关键词： Smartphones

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Advanced Situational Graphs for Robot Navigation in Structured Indoor Environments

arXiv

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arXiv 2022年

作者： Bavle, Hriday Sanchez-Lopez, Jose Luis Shaheer, Muhammad Civera, Javier Voos, Holger The Automation and Robotics Research Group Interdisciplinary Centre for Security Reliability and Trust University of Luxembourg Luxembourg The Faculty of Science Technology and Medicine University of Luxembourg Luxembourg Luxembourg I3A Universidad de Zaragoza Spain

Mobile robots extract information from its environment to understand their current situation to enable intelligent decision making and autonomous task execution. In our previous work [1], we introduced the concept of Situation Graphs (S-Graphs) which combines in a single optimizable graph, the robot keyframes and the representation of the environment with geometric, semantic and topological abstractions. Although S-Graphs were built and optimized in real-time and demonstrated state-of-the-art results, they are limited to specific structured environments with specific hand-tuned dimensions of rooms and corridors. In this work, we present an advanced version of the Situational Graphs (S-Graphs+), consisting of the five layered optimizable graph that includes (1) metric layer along with the graph of free-space clusters (2) keyframe layer where the robot poses are registered (3) metric-semantic layer consisting of the extracted planar walls (4) novel rooms layer constraining the extracted planar walls (5) novel floors layer encompassing the rooms within a given floor level. S-Graphs+ demonstrates improved performance over S-Graphs efficiently extracting the room information while simultaneously improving the pose estimate of the robot, thus extending the robots situational awareness in the form of a five layered environmental model. Video Link: https://***/zPbPe9JXgKk © 2022, CC BY.

关键词： Floors

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Performance Evaluation of Nonlinear Effects in Frequency-Splitting SWIPT Signals 91

Performance Evaluation of Nonlinear Effects in Frequency-Spl...

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91st IEEE Vehicular technology Conference, VTC Spring 2020

作者： Rajaram, Akashkumar Dinis, Rui Madeira, Joao Jayakody, Dushantha Nalin K. Beko, Marko New University of Lisbon Faculty of Science and Technology Portugal National Research Tomsk Polytechnic University School of Computer Science and Robotics Russia Universidade Lusòfona Copelabs Lisbon Portugal

ISBN: (纸本)9781728152073

Simultaneous wireless information and power transmission (SWIPT) is one of the popular technique used in radio frequency energy harvesting (EH). Frequency splitting based SWIPT (FS-SWIPT) is a novel SWIPT technique that can be adopted with frequency domain multiple access signal transmission protocol for the near field EH application in biomedical sensors. In this paper, we implement FS-SWIPT in orthogonal frequency division multiplexed (OFDM) signal, the OFDM signal has separate sub carriers for the data symbols and the energy carrying symbols. At the receiver, the energy and information symbols are based on their sub carriers by using FS-SWIPT technique. The amplification of high energy OFDM signal at transmitter by using a high power amplifier are susceptible to non linear distortion (NLD), which degrades the bit error rate (BER) performance. We analyze the impact of NLD on the BER performance of FS-SWIPT and validate the analytical results by using simulations. © 2020 IEEE.

关键词： Energy harvesting

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Self-supervised depth estimation to regularise semantic segmentation in knee arthroscopy 23rd

Self-supervised depth estimation to regularise semantic segm...

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23rd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2020

作者： Liu, Fengbei Jonmohamadi, Yaqub Maicas, Gabriel Pandey, Ajay K. Carneiro, Gustavo Australian Institute for Machine Learning School of Computer Science University of Adelaide Adelaide Australia School of Electrical Engineering and Robotics Science and Engineering Faculty Queensland University of Technology Brisbane Australia

ISBN: (纸本)9783030597092

Intra-operative automatic semantic segmentation of knee joint structures can assist surgeons during knee arthroscopy in terms of situational awareness. However, due to poor imaging conditions (e.g., low texture, overexposure, etc.), automatic semantic segmentation is a challenging scenario, which justifies the scarce literature on this topic. In this paper, we propose a novel self-supervised monocular depth estimation to regularise the training of the semantic segmentation in knee arthroscopy. To further regularise the depth estimation, we propose the use of clean training images captured by the stereo arthroscope of routine objects (presenting none of the poor imaging conditions and with rich texture information) to pre-train the model. We fine-tune such model to produce both the semantic segmentation and self-supervised monocular depth using stereo arthroscopic images taken from inside the knee. Using a data set containing 3868 arthroscopic images captured during cadaveric knee arthroscopy with semantic segmentation annotations, 2000 stereo image pairs of cadaveric knee arthroscopy, and 2150 stereo image pairs of routine objects, we show that our semantic segmentation regularised by self-supervised depth estimation produces a more accurate segmentation than a state-of-the-art semantic segmentation approach modeled exclusively with semantic segmentation annotation. © Springer Nature Switzerland AG 2020.

关键词： Semantic Segmentation

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Fault Diagnosis of Machines Operating in Variable Conditions Using Artificial Neural Networks Trained Only with Signals from an Undamaged Machine

SSRN

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SSRN 2022年

作者： Pawlik, Pawel Kania, Konrad Przysucha, Bartosz Department of Mechanics and Vibroacoustics Faculty of Mechanical Engineering and Robotics AGH University of Science and Technology al. A. Mickiewicza 30 Kraków30-059 Poland Department of Quantitative Methods in Management Faculty of Management Lublin University of Technology ul. Nadbystrzycka 38 D Lublin20-618 Poland

The fault diagnosis of machines operating in variable conditions requires special dedicated methods. Variable load, temperature or rotational speed conditions affect the vibration signal values. The article presents a new approach to diagnosing rotating machines using an artificial neural network. The new method is characterised by the artificial neural network being trained only by signals from an undamaged machine. The result of the applied approach is the generation of values for a proposed diagnostic parameter rDPNS as a function of the order of the machine shaft. The obtained spectrum of orders of this parameter allows for identifying faults following vibroacoustic diagnostic theory. The presented work analyses the use of the proposed method to diagnose misalignment and unbalance individually, as well as simultaneous misalignment and unbalance. The results of an experiment carried out in the laboratory demonstrated the effectiveness of the proposed method. © 2022, The Authors. All rights reserved.

关键词： Failure analysis

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Fusion Dynamical Systems with Machine Learning in Imitation Learning: A Comprehensive Overview

arXiv

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arXiv 2024年

作者： Hu, Yingbai Abu-Dakka, Fares J. Chen, Fei Luo, Xiao Li, Zheng Knoll, Alois Ding, Weiping Multi-Scale Medical Robotics Centre Ltd. The Chinese University of Hong Kong Hong Kong School of Computation Information and Technology Technical University of Munich Munich85748 Germany Electronic and Computer Science Department Faculty of Engineering Mondragon Unibertsitatea Arrasate20500 Spain Department of Mechanical and Automation Engineering The Chinese University of Hong Kong Hong Kong Department of Surgery The Chinese University of Hong Kong Hong Kong School of Information Science and Technology Nantong University Nantong226019 China

Imitation Learning (IL), also referred to as Learning from Demonstration (LfD), holds significant promise for capturing expert motor skills through efficient imitation, facilitating adept navigation of complex scenarios. A persistent challenge in IL lies in extending generalization from historical demonstrations, enabling the acquisition of new skills without re-teaching. Dynamical system-based IL (DSIL) emerges as a significant subset of IL methodologies, offering the ability to learn trajectories via movement primitives and policy learning based on experiential abstraction. This paper emphasizes the fusion of theoretical paradigms, integrating control theory principles inherent in dynamical systems into IL. This integration notably enhances robustness, adaptability, and convergence in the face of novel scenarios. This survey aims to present a comprehensive overview of DSIL methods, spanning from classical approaches to recent advanced approaches. We categorize DSIL into autonomous dynamical systems and non-autonomous dynamical systems, surveying traditional IL methods with low-dimensional input and advanced deep IL methods with high-dimensional input. Additionally, we present and analyze three main stability methods for IL: Lyapunov stability, contraction theory, and diffeomorphism mapping. Our exploration also extends to popular policy improvement methods for DSIL, encompassing reinforcement learning, deep reinforcement learning, and evolutionary strategies. The primary objective is to expedite readers' comprehension of dynamical systems' foundational aspects and capabilities, helping identify practical scenarios and charting potential future directions. By offering insights into the strengths and limitations of dynamical system methods, we aim to foster a deeper understanding among readers. Furthermore, we outline potential extensions and enhancements within the realm of dynamical systems, outlining avenues for further exploration. © 2024, CC BY.

关键词： Reinforcement learning

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Robotic Vision for Human-Robot Interaction and Collaboration: A Survey and Systematic Review

arXiv

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arXiv 2023年

作者： Robinson, Nicole Tidd, Brendan Campbell, Dylan Kulić, Dana Corke, Peter Australian Research Council Centre of Excellence for Robotic Vision School of Electrical Engineering & Robotics QUT Centre for Robotics Queensland University of Technology Faculty of Engineering Turner Institute for Brain and Mental Health Monash University 18 Alliance Lane ClaytonVIC3800 Australia Australian Research Council Centre of Excellence for Robotic Vision School of Electrical Engineering & Robotics QUT Centre for Robotics Queensland University of Technology 2 George Street BrisbaneQLD4000 Australia Visual Geometry Group Department of Engineering Science University of Oxford 17 Parks Road Oxford OxfordshireOX1 3PJ United Kingdom Australian Research Council Centre of Excellence for Robotic Vision Faculty of Engineering Monash University 18 Alliance Lane ClaytonVIC3800 Australia

Robotic vision for human-robot interaction and collaboration is a critical process for robots to collect and interpret detailed information related to human actions, goals, and preferences, enabling robots to provide more useful services to people. This survey and systematic review presents a comprehensive analysis on robotic vision in human-robot interaction and collaboration over the last 10 years. From a detailed search of 3850 articles, systematic extraction and evaluation was used to identify and explore 310 papers in depth. These papers described robots with some level of autonomy using robotic vision for locomotion, manipulation and/or visual communication to collaborate or interact with people. This paper provides an in-depth analysis of current trends, common domains, methods and procedures, technical processes, data sets and models, experimental testing, sample populations, performance metrics and future challenges. This manuscript found that robotic vision was often used in action and gesture recognition, robot movement in human spaces, object handover and collaborative actions, social communication and learning from demonstration. Few high-impact and novel techniques from the computer vision field had been translated into human-robot interaction and collaboration. Overall, notable advancements have been made on how to develop and deploy robots to assist people. Copyright © 2023, The Authors. All rights reserved.

关键词： Human robot interaction

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