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IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： M. R. Dindarloo A. S. Mirjalili S. A. Khalilpour R. Khorrambakht Stephan Weiss H. D. Taghirad Advanced Robotics and Automated Systems (ARAS) Faculty of Electrical Engineering K. N. Toosi University of Technology Tehran Iran Department of Electrical and Computer Engineering Tandon School of Engineering Control/Robotics Research Laboratory New York University Brooklyn NY Department of Smart Systems Technologies University of Klagenfurt Austria

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

The efficient operation of large-scale Cable-Driven Parallel Robots (CDPRs) relies on precise calibration of kinematic parameters and the simplicity of the calibration process. This paper presents a graph-based self-calibration framework that explicitly addresses cable sag effects and facilitates the calibration procedure for large-scale CDPRs by only relying on internal sensors. A unified factor graph is proposed, incorporating a catenary cable model to capture cable sagging. The factor graph iteratively refines kinematic parameters, including anchor point locations and initial cable length, by considering jointly onboard sensor data and the robot’s kineto-static model. The applicability and accuracy of the proposed technique are demonstrated through Finite Element (FE) simulations, on both large and small-scale CDPRs subjected to significant initialization perturbations.

关键词： Meters Accuracy Perturbation methods Kinematics Robot sensing systems End effectors Software Calibration Sensors Finite element analysis

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Design Method for Series-Fed Omnidirectional Filtenna Based on Full-Metal 3-D Printing

Design Method for Series-Fed Omnidirectional Filtenna Based ...

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Cross Strait Quad-Regional Radio Science and Wireless Technology Conference (CSRWTC)

作者： Shu-Qing Zhang Shu-Ting Wu Sai-Wai Wong Yejun He Zhonghe Zhang Xuzhou Yu State Key Laboratory of Radio Frequency Heterogeneous Integration Shenzhen Key Laboratory of Antennas and Propagation Guangdong Engineering Research Center of Base Station Antennas and Propagation College of Electronics and Information Engineering Shenzhen University China The Department of Electrical and Computer Engineering Faculty of Science and Technology University of Macau Macau SAR China

ISBN: (数字)9798331507794

ISBN: (纸本)9798331507800

This paper proposed a design approach for a series-fed omnidirectional antenna based on 3D full-metal printing. A major issue when designing series-fed antennas is the radiation pattern lobing caused by the unique feeding mechanism. In this paper, necessary adjustments are made based on the phase relationships between the currents and electric fields of each radiating element, resulting in improved radiation characteristics for the series-fed antenna. To validate this idea, the paper designs a rod-shaped full-metal omnidirectional antenna, achieving a wide operating bandwidth and high gain. Additionally, a filtering antenna with omnidirectional radiation is designed, which achieves a high level of out-of-band suppression as well as good omnidirectional radiation performance.

关键词： Wireless communication Phased arrays Filtering Design methodology Omnidirectional antennas Bandwidth Three-dimensional printing Antenna feeds Electric fields Antenna radiation patterns

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A Comparative Analysis of BLE V.5 and BLE V.4 Communication Protocols for Multi-Agent Rescue Robots under Rayleigh Fading Channel

A Comparative Analysis of BLE V.5 and BLE V.4 Communication ...

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RSI/ISM International Conference on Robotics and Mechatronics (ICROM)

作者： Armin Javadi Rayeheh Niroomanesh Mohammad Ghamari Khalil Alipour Bahram Tarvirdizadeh Department of Mechatronics Engineering Faculty of New Sciences and Technologies Advanced Service Robots (ASR) Laboratory University of Tehran Tehran Iran Department of Electrical and Computer Engineering Kettering University Flint Michigan USA

This article presents a thorough evaluation of the applicability of Bluetooth Low Energy (BLE) version 5 as a communication protocol for multi-agent systems in search and rescue missions. The study extensively investigates the energy efficiency and reliability aspects of BLE v.5.3 to facilitate effective communication among multiple robots in such scenarios. A key focus of the research is the simulation of the advertising mode of BLE in the challenging presence of the Rayleigh fading channel, which is inevitable in the search and rescue environment. Furthermore, a comprehensive analysis is conducted by comparing BLE v.5.3 with the previous version, BLE v.4, with specific emphasis on energy efficiency and throughput metrics. Additionally, the study delves into the investigation of packet collision phenomena within the advertising mode of BLE v.5.3, shedding light on energy consumption, throughput performance, and the probability of packet collision. The findings of this study provide valuable insights for the design and implementation of communication systems within comparable scenarios.

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Blood Pressure Estimation through Photoplethysmography and Machine Learning Models

Blood Pressure Estimation through Photoplethysmography and M...

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International Conference on Control, Instrumentation, and Automation

作者： Hanieh Mohammadi Bahram Tarvirdizadeh Khalil Alipour Mohammad Ghamari Department of Mechatronics Engineering Advanced Service Robots (ASR) Laboratory Faculty of New Sciences and Technologies University of Tehran Tehran Iran Department of Electrical and Computer Engineering Kettering University Flint Michigan USA

Blood pressure (BP) is a crucial health element, the fluctuations of which may have profound implications for an individual's well-being. Traditional methods of measuring BP, such as cuff-based and invasive devices, are not only uncomfortable but also unable to provide continuous monitoring. In response to this need, we propose a cuffless, continuous, and noninvasive BP measurement system utilizing photoplethysmograph (PPG) signals and machine learning (ML) models. PPG, an optical volumetric measurement technique, can identify alterations in blood volume within the tissue's vascular network. In this study, PPG signals obtained from diverse individuals underwent preprocessing and feature extraction. Subsequently, a feature selection technique was employed to identify suitable features. These selected features were then employed to train and evaluate ML models. Ultimately, we identified optimal regression models for independent estimation of diastolic blood pressure (DBP) and systolic blood pressure (SBP). Our findings indicate that the random forest (RF) model, in combination with the SelectFromModel feature selection method, outperformed other models. This model yielded significant outcomes, achieving a root mean square error (RMSE) of 6.61 for DBP and 10.06 for SBP, highlighting its superior performance in BP estimation.

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Vascular Age Prediction with PPG-Based LSTM Model

Vascular Age Prediction with PPG-Based LSTM Model

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International Conference on Control, Instrumentation, and Automation

作者： Kiana Pilevar Abrisham Khalil Alipour Bahram Tarvirdizadeh Mohammad Ghamari Department of Mechatronics Engineering Advanced Service Robots (ASR) Laboratory Faculty of New Sciences and Technologies University of Tehran Tehran Iran Department of Electrical and Computer Engineering Kettering University Flint Michigan USA

Vascular aging encompasses structural and functional changes in blood vessels associated with aging, including increased stiffness, reduced elasticity, and atherosclerosis development. These changes contribute to cardiovascular diseases (CVDs), a global health challenge necessitating precise assessment methods. Evaluating vascular age involves comparing blood vessel health to chronological age, offering insights into arterial stiffness for potential cardiovascular disease prevention. In this study, we introduce an approach using Long Short-Term Memory (LSTM) models for vascular age prediction. Leveraging simulated Photoplethysmogram (PPG) waveforms from the radial artery and a diverse sample of healthy adults aged 25 to 75, our method offers a non-invasive, cost-effective means of health evaluation. Following 5-fold cross-validation, the LSTM-based model demonstrated significant performance, with an average test accuracy, precision, recall, and F1 Score of approximately 97%. This innovative approach, with its non-invasive nature, minimal power consumption, and user-friendly interface, showcases the potential of PPG technology's integration into various devices, such as fitness trackers, smartphones, and tablets, ensuring its widespread accessibility and applicability in real-world health assessments. Accurate vascular age prediction aids in identifying cardiovascular aging deviations and underlying disorders, advancing assessment methods and contributing to proactive cardiovascular health management.

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Predicting Vascular Age using PPG Signals and Machine Learning Algorithms: A Non-Invasive Approach for Early Cardiovascular Risk Detection

Predicting Vascular Age using PPG Signals and Machine Learni...

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RSI/ISM International Conference on Robotics and Mechatronics (ICROM)

作者： Kiana Pilevar Abrisham Khalil Alipour Bahram Tarvirdizadeh Mohammad Ghaman Department of Mechatronics Engineering Faculty of New Sciences and Technologies Advanced Service Robots (ASR) Laboratory University of Tehran Tehran Iran Department of Electrical and Computer Engineering Kettering University Flint Michigan USA

Cardiovascular diseases (CVDs) pose a significant global health challenge, necessitating effective strategies for early risk assessment and intervention. Arterial stiffness, a critical parameter within the cardiovascular system, is considered a primary risk factor for CVD development. This parameter undergoes natural age-related structural and functional changes in arterial walls, resulting in increased arterial stiffness and reduced elasticity. These changes contribute to vascular aging and alter pulse wave velocity. Photoplethysmography (PPG) offers a non-invasive means to assess these alterations. Our research leverages PPG in combination with machine learning to develop a portable, non-invasive method for predicting vascular age. We identify and select 21 features from the fiducial points of the digital artery PPG signals obtained from simulated pulse waves across a diverse sample of healthy adults aged 25 to 75 years, its first derivative, and its second derivative waveforms. We assess the performance of machine learning algorithms, including Decision Tree, k-Nearest Neighbors (KNN), and Support Vector Machine (SVM). Among these algorithms, SVM outperformed the others, achieving an accuracy, precision, recall, and F1 score of 99%. This high accuracy underscores the potential of SVM in predicting vascular age. Accurate vascular age prediction within the healthy population has the potential to establish age-specific benchmarks, aiding in the detection of outliers indicative of accelerated cardiovascular aging or underlying cardiovascular diseases.

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Adaptive position tracking control of the lower limb exoskeleton robot with an uncertain dynamic model 18

Adaptive position tracking control of the lower limb exoskel...

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18th IEEE Conference on Industrial Electronics and Applications, ICIEA 2023

作者： Yuan, Ting Zhang, Chi Yi, Feng Lv, Pingping Li, Shupei Zhang, Meitong Ningbo University Ningbo Instituteof Materials Technology and Engineering Chinese Academy of Sciences Faculty of Electrical Engineering and Computer Science Ningbo315201 China Chinese Academy of Sciences Zhejiang Key Laboratory of Robotics and Intelligent Manufacturing Equipment Technology Ningbo Institute of Materials Technology and Engineering Ningbo315201 China University of Chinese Academy of Sciences Ningbo Institute of Materials Technology and Engineering Chinese Academy of Sciences College of Materials Science and Opto-Electronic Technology Ningbo315201 China Hebei University of Science and Technology Ningbo Institute of Materials Technology and Engineering Chinese Academy of Sciences School of Electrical Engineering Ningbo315201 China

ISBN: (纸本)9798350312201

In this paper, an adaptive position control method combining proportional-derivative (PD) control, RBF neural network-based sliding mode (SM) control, and feedforward (FF) control, i.e., PD-FF-SM control, is proposed to deal with the dynamic uncertainties, disturbances, and slow response in lower limb exoskeleton robot system. The Lagrange method is utilized to establish dynamic models that ignore the uncertainties and disturbances in the swing phase and supporting phase. Then, the PD feedback controller is designed with a sliding surface function, to keep the system stable. The FF controller is adopted to improve the response by using dynamic models. And the RBF neural network-based SM controller is designed to compensate for the uncertainties and disturbances. The system's stability is verified by Lyapunov's theorem. The simulation results show that the proposed control method can effectively reduce the error of position tracking and response time with inaccurate dynamic modeling. © 2023 IEEE.

关键词： Sliding mode control

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Speech Emotion Recognition: A Brief Review of Multi-modal Multi-task Learning Approaches

Speech Emotion Recognition: A Brief Review of Multi-modal Mu...

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International Conference on Advanced engineering Theory and Applications, AETA 2022

作者： Pham, Nhat Truong Tran, Anh-Tuan Pham, Bich Ngoc Hong Dang-Ngoc, Hanh Nguyen, Sy Dzung Dang, Duc Ngoc Minh Division of Computational Mechatronics Institute for Computational Science Ton Duc Thang University Ho Chi Minh City Viet Nam Faculty of Electrical and Electronics Engineering Ton Duc Thang University Ho Chi Minh City Viet Nam Faculty of Information Technology Ho Chi Minh City Open University Ho Chi Minh City Viet Nam Department of Telecommunications Engineering Ho Chi Minh City University of Technology Ho Chi Minh City Viet Nam Laboratory for Computational Mechatronics Institute for Computational Science and Artificial Intelligence Van Lang University Ho Chi Minh City Viet Nam Faculty of Mechanical–Electrical and Computer Engineering Van Lang University Ho Chi Minh City Viet Nam Computing Fundamental Department FPT University Ho Chi Minh Viet Nam

ISBN: (纸本)9789819987023

Speech emotion recognition (SER) has become an attention-grabbing topic in recent years thanks to the development of deep learning in the field of speech processing. However, it is difficult to recognize an accurate emotional state from only speech signals. Therefore, researchers have investigated multi-modalities such as speech, visual, and text inputs to improve the emotional recognition rate of speech. In addition, to enhance the generalized deep learning models for SER, multi-task learning (MTL) strategies have also been applied in the past decade. In this paper, a brief and comprehensive review of multi-modal multi-task learning (3MTL) approaches for recognizing emotional states from speech signals is presented, including multi-modal SER, multi-task learning SER, and multi-modal multi-task learning SER. This paper also discusses about some problems that still need to be solved in 3MTL SER and gives some suggestions for the future. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Emotion Recognition

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Pattern Transformation of Low-Profile Multi-Mode Antenna for A Phased Array with Simultaneous Wide-Angle Scanning and High-Gain Properties

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IEEE Transactions on Antennas and Propagation 2025年

作者： Yan, Qi-Long Liu, Neng-Wu Zhu, Lei Yun, Yu Liu, Ying Xidian University National Key Laboratory of Radar Detection and Sensing Xi'an710071 China University of Macau Faculty of Science and Technology Department of Electrical and Computer Engineering China Shaanxi University of Science & Technology School of electronic information and artificial intelligence Xi'an710021 China

In this article, a novel multi-mode design approach for pattern transformation of low-profile multi-mode microstrip patch antenna (MPA) has been proposed and developed, aiming to simultaneously achieve the wide-angle scanning and high-gain properties for a phased array. Herein, the TM00, TM01, TM20, and TM21 modes of the MPA are employed. Firstly, the working principle about how to move these four modes closely to each other in resonant frequency is deeply studied, the results prove that the shorting pins and slots could be loaded on the radiator for frequency reallocation of these four modes. Secondly, the radiation pattern transformation of the MPA at TM00, TM20, and TM21 modes are deeply investigated, which demonstrates that the non-broadside beam of its TM21 mode could be reshaped into the broadside one, and the omnidirectional pattern of its TM00 mode could be reshaped into the dual beam at yoz-plane. Most importantly, the radiation pattern of its TM20 mode could be rotated into the dual-beam with co-polarized Eθ component at yoz-plane. With these arrangements, the broadside-beam and dual-beam could be excited under same frequency at different modes. Thirdly, based on these two beams with different phases at two ports, the antenna element has successfully gained the improved beam scanning and gain performance simultaneously. Fourthly, the proposed multi-mode array is arranged in a triangular grid. By controlling the phase difference between these ports, the antenna could achieve both wide-beam scanning and high gain. Experimental results show that the antenna element has an impedance bandwidth (|S11| © 1963-2012 IEEE.

关键词： Antenna phased arrays

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Anomaly Detection Based on Principle of Justifiable Granularity and Probability Density Estimation

Anomaly Detection Based on Principle of Justifiable Granular...

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2023 China Automation Congress, CAC 2023

作者： Du, Sheng Ma, Xian Li, Xiang Wu, Min Cao, Weihua Pedrycz, Witold School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China University of Alberta Department of Electrical and Computer Engineering EdmontonABT6G 2R3 Canada Systems Research Institute Polish Academy of Sciences Warsaw00-901 Poland Istinye University Faculty of Engineering and Natural Sciences Department of Computer Engineering Istanbul Sariyer Turkey

ISBN: (纸本)9798350303759

Anomaly detection is essential to ensure the safety of industrial processes. This paper presents an anomaly detection approach based on the probability density estimation and principle of justifiable granularity. First, time series data are transformed into a two-dimensional information granule by the principle of justifiable granularity. Then, the test statistic is constructed, and the probability density and cumulative distribution functions of the test statistic are calculated. Next, the confidence level determines the test threshold. Finally, the time series data of a key parameter in the sintering process is used as a case study. The experimental result demonstrates that the proposed approach can detect abnormal time series data effectively, providing an accurate and effective solution for detecting time series anomalies in industrial processes. © 2023 IEEE.

关键词： Time series

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