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SSRN 2023年

作者： Yeo, Chaebeom Chang, Yeonhee Song, Cheol Daegu Gyeongbuk Institute of Science and Technology Department of Robotics and Mechatronics Engineering Daegu42988 Korea Republic of

Background: Although several optical systems have been developed for monitoring the tissue metabolic rate of oxygen consumption (tMRO2) measurement, there are some limitations in terms of system design, image acquisition speed, and clinical application. In this study, we present and validate a multimodal optical system combining diffuse speckle contrast analysis (DSCA) and near-infrared spectroscopy (NIRS) with a unique system design for high-speed tMRO2 ***: The optical system for simultaneous multiple-wavelength illumination and detection by a single camera, is constructed using dichroic mirrors without an external trigger device so that it achieves fast image-acquisition speed. To validate system performance, flow and liquid phantom experiments and an in-vivo arterial occlusion tests are conducted by varying the camera exposure time from 0.5 to 10 ms. We analyze and compare the results according to the exposure time to acquire the optimal tMRO2 signal by dual-exposure time ***: From the flow phantom experiment, the blood flow index (BFI) changes measured by DSCA modality and results showed that the highest linearity and sensitivity were confirmed at the shortest exposure time. From liquid phantom experiments, NIRS modality confirmed high sensitivity and measurement range consistent of tissue oxygenation index (TOI) at the longest exposure time. From the in-vivo experiment, it was confirmed that BFI and TOI signals from the two modalities had a trade-off with the exposure time. We obtained the optimal tMRO2 using dual-exposure time ***: We conclude that the proposed DSCA/NIRS provides real-time tMRO2 assessment, which can provide biomarkers for diagnosing vascular diseases. © 2023, The Authors. All rights reserved.

关键词： Tissue

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Comparative Study of Energy Management Techniques for Solar PV-Based Microgrid Systems

Comparative Study of Energy Management Techniques for Solar ...

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engineering and Technology (PICET), Parul International Conference on

作者： Yaya Kamagaté Heli Amit Shah SSPM Sharma B Electrical Engineering Department Parul University Vadodara India Robotics and Automation Engineering Department Parul University Vadodara India Mechatronics Engineering Department Symbiosis University of Applied Sc. Indore India

ISBN: (数字)9798350369748

ISBN: (纸本)9798350369755

In recent years, microgrid systems have gained popularity as reliable, efficient, and clean energy sources for local communities. Among these, solar PV systems stand out as a widely used microgrid variant. However, the intermittent nature of solar power necessitates the incorporation of energy storage solutions to ensure a consistent electricity supply. In this context, batteries and supercapacitors emerge as two prominent options for storing energy in solar PV microgrids. This study leads a comprehensive examination and correlation of three distinct solar PV-based microgrid configurations: solar PV system (PVS), solar PV with battery system (PVBS), and solar PV with both battery and supercapacitor system (PVBSS). Employing MATLAB/Simulink, the analysis centers on their technical capabilities, particularly emphasizing energy management. The simulation results demonstrate that incorporating battery storage enhances the performance of the PVS microgrid, ensuring the stability of the DC bus voltage and thus balancing energy production and consumption. Furthermore, the PVBSS configuration exhibits superior performance through its capacity to deliver high power with rapid response times, consequently extending the battery lifespan. This investigation underscores the critical role of energy storage solutions in enhancing solar PV microgrids' effectiveness and overall performance.

关键词： Simulation Microgrids Voltage Production Supercapacitors Stability analysis Batteries Time factors Reliability Energy management

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Learning flatness-based controller using neural networks

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ASME Letters in Dynamic Systems and Control 2021年第2期1卷 021003页

作者： Ren, Hailin Qi, Jingyuan Ben-Tzvi, Pinhas Robotics and Mechatronics Lab Department of Mechanical Engineering Virginia Tech BlacksburgVA24060 United States Department of Physics Virginia Tech BlacksburgVA24060 United States

This paper presents a method to imitate flatness-based controllers for mobile robots using neural networks. Sample case studies for a unicycle mobile robot and an unmanned aerial vehicle (UAV) quadcopter are presented. The goals of this paper are to (1) train a neural network to approximate a previously designed flatness-based controller, which takes in the desired trajectories previously planned in the flatness space and robot states in a general state space, and (2) present a dynamic training approach to learn models with high-dimensional inputs. It is shown that a simple feedforward neural network could adequately compute the highly nonlinear state variables transformation from general state space to flatness space and replace the complicated designed heuristic to avoid singularities in the control law. This paper also presents a new dynamic training method for models with high-dimensional independent inputs, serving as a reference for learning models with a multitude of inputs. Training procedures and simulations are presented to show both the effectiveness of this novel training approach and the performance of the welltrained neural network. Copyright © 2021 by ASME.

关键词： Machine learning

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Biologically Inspired Networking (BIN): Leveraging Neurobiological Principles for Adaptive, Scalable, and Efficient Communication

Biologically Inspired Networking (BIN): Leveraging Neurobiol...

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International Conference on Computing, Networking and Communications (ICNC)

作者： Razvan Cristian Voicu Amanda Frischmann Muhammad Hassan Tanveer Amir Ali Amiri Moghadam Yannique Tello Gabriela Oprea-Ilies Yusun Chang Department of Robotics & Mechatronics Engineering Kennesaw State University Atlanta Georgia Windship Cancer Institute Emory University School of Medicine Atlanta Georgia

ISBN: (数字)9798331520960

ISBN: (纸本)9798331520977

The surge in interconnected applications, particularly in AI, IoT, and intelligent infrastructure, imposes new demands on communication networks, requiring them to handle high data volumes, support real-time exchanges, and dynamically adapt to fluctuating conditions. Traditional networking models, reliant on centralized processing and static protocols, are insufficient to meet these evolving needs, resulting in inefficiencies, latency, and scalability issues. This paper introduces a biologically inspired networking paradigm that mimics neurobiological principles such as event-driven communication, distributed intelligence, and adaptive resource management. By conceptualizing data types as analogous to neurotransmitters and infrastructure learning as synaptic plasticity, the framework provides a dynamic, scalable solution that enhances efficiency and resilience. The proposed model is particularly suited for resource-constrained environments, dynamically optimizing resource allocation and communication pathways in real time. Simulations demonstrate significant improvements in latency, resource utilization, scalability, and reliability, proving its potential as a foundation for next-generation networks.

关键词： Adaptation models Adaptive systems Biological system modeling Scalability Real-time systems Resource management Internet of Things Artificial intelligence Surges Resilience

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High-Precision 3-DOF Compliant Positioning Stage for Large Range Micro-Manipulation Applications

High-Precision 3-DOF Compliant Positioning Stage for Large R...

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IEEE International Conference of Intelligent Robotic and Control engineering (IRCE)

作者： Ashenafi Abrham Kassa Bijan Shirinzadeh Julian Smith Department of Mechanical and Aerospace Engineering Robotics and Mechatronics Research Laboratory (RMRL) Monash University Melbourne Australia Department of Surgery Monash University Melbourne Australia

ISBN: (数字)9798350352399

ISBN: (纸本)9798350352405

This paper introduces a novel high-precision compliant mechanism-based 3-degree-of-freedom (3-DOF) positioning stage with a large range and planar layout. The design incorporates a cartwheel revolute flexure and compound basic parallelogram (CBP) prismatic flexure modules arranged in series to establish a PPR-kinematic chain. Three such kinematic chains are symmetrically arranged at 120° to each other around the output platform. This design ensures large deformation and high dynamic performance while minimizing cross-coupling and parasitic motion. The compliance matrix method (CMM) is utilized to establish the stiffness model of the designed mechanism. Computational analysis is performed to validate the developed analytical model. Moreover, the reachable workspace, inverse kinematics, and dynamic performance of the proposed stage are investigated. A workspace of 4.6 mm × 5.1 mm × 83 mrad is achieved while maintaining a high natural frequency of 58 Hz. From the analysis, the proposed stage can be adopted in micro-manipulation applications that require high-precision motion over an extended range.

关键词： Transmission line matrix methods Symmetric matrices 3-DOF Dynamics Layout Kinematics Fasteners Manufacturing Motion control Robots

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Emotion Recognition Through EEG Signals With Movie Clips Stimuli

Emotion Recognition Through EEG Signals With Movie Clips Sti...

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Electrics and Computer (INTCEC), Interdisciplinary Conference on

作者： Jonathan Axel Cruz Vazquez Jesús Yaljá Montiel Pérez Rodolfo Romero Herrera Robotics and mechatronics laboratory IPN – CIC CDMX México Department of Computer Science and Engineering IPN – ESCOM CDMX México

ISBN: (数字)9798350349450

ISBN: (纸本)9798350349467

This study proposes a multimodal emotion recognition method acquiring electroencephalogram (EEG) data and using movie clips to express emotional stimuli. The study included 12 participants who aimed to identify three emotions: happy, sad, and neutral. For the experiments, the Emotiv Epoc+ device was used for data collection, including data preprocessing, time and frequency domain feature extraction, and classification. Emotion recognition uses different machine learning algorithms, including support vector machines (SVM), k-nearest neighbors (k-NN), random forests, and neural networks. The algorithm is trained and evaluated using feature vectors extracted from participants' emotional responses to movie videos. This method achieves a competitive accuracy of 79.09% using an SVM(POL) classifier and features including time and frequency domains.

关键词： Support vector machines Emotion recognition Visualization Accuracy Machine learning algorithms Frequency-domain analysis Feature extraction

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Conceptualization of a Hybrid Machine Combining Laser Beam Micro Machining (LBMM) and Micro Electrical Discharge Machining (Micro-EDM) in a Single Setup

Conceptualization of a Hybrid Machine Combining Laser Beam M...

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International Conference on mechatronics (ICOM)

作者： Wan Ahmad Bin Wan Azhar Tanveer Saleh Autonomous Systems and Robotics Research Unit Department of Mechatronics Engineering International Islamic University Malaysia Jalan Gombak Kuala Lumpur Malaysia

ISBN: (数字)9798350349788

ISBN: (纸本)9798350349795

The utilization of hybrid laser beam micro machining (LBMM) in conjunction with micro electrical discharge machining $(\mu\text{EDM})$ has gained widespread popularity due to its ability to improve material removal rates and enhance surface quality. Typically, these processes occur on separate machines, resulting in drawbacks such as time loss during workpiece transfer, potential misalignment issues, and increased risks of sample damage during the transfer. This research provides a system and method for a two-step sequential machining process of LBMM and $\mu\text{EDM}$ that allows the workpiece to remain at the same location for both processes. A LBMM process is used for drilling a rough blind hole, followed by $\mu\text{EDM}$ for the finishing process. The workpiece is fixed and positioned in the $\mu\text{EDM}$ workstation. A microscopic camera, which is mounted on the $\mu\text{EDM}$ machine, is used to provide common coordinate position data for the laser and $\mu\text{EDM}$ machine. This coordinate is used by the $\mu\text{EDM}$ machine to position the electrode perfectly on top of LBMM hole before machining. The results suggest that LBMM- $\mu\text{EDM}$ machining can reduce machining time while achieving good hole quality and repeatability. The hybrid sequential process significantly reduces drilling time, being about 1.55 times faster than the pure $\mu\text{EDM}$ [method. However, the findings also indicate that it is not necessary to use LBMM- $\mu\text{pEDM}$ for low aspect ratio holes. This concept enables the workpiece to stay in one position throughout both processes, eliminating any time loss and damage during transfer, as well as avoiding misalignment issues.

关键词： Drilling mechatronics Surface discharges Microscopy Surface emitting lasers Machining Micromachining

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Modular Multi-axis Elastic Actuator with Torque Sensing Capable p-CFH for Highly Impact Resistive Robot Leg

Modular Multi-axis Elastic Actuator with Torque Sensing Capa...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Youngrae Kim Sunghyun Choi Jinhyeok Song Dongwon Yun Department of Robotics and Mechatronics Engineering Daegu Gyeongbuk Institute of Science and Technology (DGIST) Daegu South Korea

This study proposes a modular Multi-axis Elastic Actuator (MAEA) for legged robots that can effectively cope with impacts that may occur during dynamic maneuvering. MAEA has multi-axis compliance and can measure the torque without additional encoders. Therefore, effective impact resistance is possible with less volume and weight than conventional Series Elastic Actuators (SEA). The 6-axis stiffness analysis of paired-Crossed Flexural Hinge (p-CFH) is extended from small deformation to large deformation, and the accuracy is verified through Finite Element Analysis (FEA) and experiments. Based on the analysis, the torque of p-CFH is measured, and feedback torque control is also performed. Finally, the robot leg was constructed with MAEA, and the multi-axis impact resistance performance of MAEA was demonstrated by analyzing the applied impact during landing experiments at various angles.

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Inpatient Monitoring System: Temperature, Oxygen Saturation, Blood Pressure, Heart Rate, and Infusion Automation Based on ESP 32, IoT, and Mobile Application

Inpatient Monitoring System: Temperature, Oxygen Saturation,...

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International Conference of Computer and Informatics engineering (IC2IE)

作者： Irvanda Joseph Patrick Anthony Winda Astuti Zener Sukra Lie Mahmud Iwan Solihin Automotive and Robotics Program Computer Engineering Department BINUS ASO School of Engineering Bina Nusantara University Jakarta Indonesia Department of Mechanical & Mechatronics Engineering UCSI University Kuala Lumpur Malaysia

ISBN: (数字)9798331505530

ISBN: (纸本)9798331505547

The implementation of a patient monitoring system and infusion automation which aims to ensure regular and periodic monitoring of inpatient conditions are applied in this system. This embedded system is applied in hospitals and addresses the uneven distribution of healthcare workers in Indonesia, particularly in remote areas. Currently, manual checks by nurses can lead to errors and reduced patient comfort. The improvement supervision is developed in this work. The system monitored body temperature, oxygen saturation, blood pressure, heart rate, and automated infusions. All the embedded systems are connected to Internet of Things (IoT) and a real-time database accessible through an application and web. This system allows doctors and hospital authorities to make decisions based on patient condition history. The testing phase of the system shows four data acquisition devices (temperature, oxygen saturation, blood pressure, and heart rate), an ESP 32, and Firebase as a database, have ability to capture and send real-time data every five seconds and can be accessed by doctors, patients, and hospital authorities.

关键词： Heart rate Temperature sensors Temperature measurement Automation Hospitals Databases Blood pressure Real-time systems Biomedical monitoring Testing

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Advancement in Smart Cane Technology: Enhancing Mobility for the Visually Impaired Using ROS and LiDAR

Advancement in Smart Cane Technology: Enhancing Mobility for...

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International Conference on robotics and Artificial Intelligence (ICRAI)

作者： Saqib Zafar Hafiz Farhan Maqbool Naveed Ahmad Arham Ali Abdul Moeizz Faizan Ali Juri Taborri Stefano Rossi Department of Economics Engineering Society and Business Organization University of Tuscia Viterbo VT Italy Department of Mechanical Mechatronics and Manufacturing Engineering University of Engineering and Technology Lahore (Faisalabad Campus) Pakistan Human-Centred Robotics Lab National Center of Robotics and Automation Pakistan

ISBN: (数字)9798350355703

ISBN: (纸本)9798350355710

Visual impairment affects the ability to navigate independently in an unknown environment due to reliance on human/dog assistance, potential miscommunication, and discomfort during mobility. To make the visually impaired (VI) individuals self-reliant and confident in their mobility the proposed system has been developed that contains a light detection and ranging (LiDAR) sensor for obstacle detection and two omni-wheels coupled with the DC gear encoder motors for precise movement in any direction without lifting the cane. Hector Simultaneous Localization and Mapping (SLAM), A *, and steering wheel algorithms have been implemented in the robot operating system (ROS) for real-time environment mapping, efficient path planning, and navigating in an unknown indoor static environment, respectively. The Raspberry Pi 3B+ and Arduino Mega 2560 are used in the master-slave configuration for decision-making on path planning and controlling the maneuverability of the system in real-time. The proposed system in the paper is successfully tested on one subject in two indoor environments. The results demonstrate that the system serves as an assistive mobile robot, helping the VI individual to navigate confidently in an unknown environment and reach the destination without assistance.

关键词： Simultaneous localization and mapping Laser radar Navigation Operating systems Decision making Visual impairment Wheels Real-time systems Path planning robotics and automation

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