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International Conference on mechatronics (ICOM)

作者： Mohammad Mainul Hasan Tanveer Saleh Ali Sophian Autonomous Systems and Robotics Research Unit (ASSRU) Department of Mechatronics Engineering International Islamic University Malaysia Kuala Lumpur Malaysia

ISBN: (数字)9798350349788

ISBN: (纸本)9798350349795

In modern manufacturing processes, precision and efficiency are paramount, particularly in a stochastic method such as Micro Electrical Discharge Machining (μEDM). With its ability to fabricate intricate geometries in hard and difficult-to-machine materials, μEDM has become indispensable in various industries. However, optimising machining time while ensuring reliability and accuracy remains a significant challenge that often relies on the intuition and experience of machinists. In response, this paper presents a comprehensive study on the modelling of machining time (MT) and also its associated uncertainty characterised by the standard deviation (SD) in the μEDM process using Response Surface Methodology (RSM). The study utilises experimental data generated through the I -optimal design of experiment technique (DOE) to develop quadratic equations for the MT Mean and SD MT models. The input factors for the models include capacitance, voltage, feed rate, tool speed, tool diameter, workpiece thickness, and workpiece materials defined by thermal conductivity, melting point, and electrical resistivity. The adequacy of both models was assessed based on ANOV A and fit statistics, demonstrating their effectiveness. Additionally, the mean percentage accuracies of the MT Mean and SD MT models are evaluated as 74.5% and 58% for the train set and 86.8% and 82.1 % for the test set, respectively. By leveraging RSM techniques, this research aims to provide insights into the complex relationships between machining parameters and the resulting machining time and uncertainty, facilitating enhanced process μEDM control and performance optimisatio n.

关键词： Training Adaptation models Uncertainty Accuracy Estimation Machining Predictive models

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Planning Under Uncertainties with Closed-Loop Sensitivity: Recent Results and Perspectives 16th

Planning Under Uncertainties with Closed-Loop Sensitivity: ...

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16th European robotics Forum, ERF 2025

作者： Belvedere, Tommaso Afifi, Amr Wasiela, Simon Pupa, Andrea CNRS Université de Rennes Inria IRISA Campus de Beaulieu Rennes France Robotics and Mechatronics Lab Faculty of Electrical Engineering Mathematics and Computer Science University of Twente Enschede Netherlands LAAS-CNRS Université de Toulouse CNRS UPS Toulouse France Department of Sciences and Methods for Engineering University of Modena and Reggio Emilia Modena Italy

ISBN: (纸本)9783031894701

This paper presents a comprehensive summary of recent advancements in motion planning under parametric uncertainties, focusing on the application of closed-loop state sensitivity. This concept provides a framework for quantifying how deviations in model parameters affect the behavior of a system in closed-loop, facilitating the generation of robust trajectories. Various methods have been proposed to improve the resilience of robotic systems to model inaccuracies. However, these approaches often face challenges such as computational complexity and limitations in real-time applications. This paper synthesizes key results from several recent works, highlighting the development of techniques that optimize trajectory robustness while reducing computational overhead. Additionally, we outline the practical applications of these methods, discussing their validation through simulations and experiments on robotic systems subject to non-negligible uncertainties in their models. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Robots

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Enhancing Industrial Safety Helmets: Development and Evaluation of Epoxy-Based Glass and Basalt Fiber Composites 1

Enhancing Industrial Safety Helmets: Development and Evaluat...

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1st International Conference on Materials Innovation in engineering and Technology, ICMIET 2024

作者： Pandi, Raja R. Bihari, Bagesh Chokkalingam, P. Karthikeyan, R. Anand, R. Kalaiarasan, S. Sivalingam, A. Department of Robotics and Automation Rajalakshmi Engineering College Tamil Nadu India Department of Mechanical Engineering Ramgarh Engineering College Jharkhand India Department of Mechanical Engineering Erode Sengunthar Engineering College Tamil Nadu India Department of Automobile Engineering Rajalakshmi Engineering College Tamil Nadu India Department of Aeronautical Engineering Nehru Institute of Technology Tamil Nadu India Department of Chemistry Sona College of Technology Tamil Nadu India Department of Mechatronics Engineering Sona College of Technology Tamil Nadu India

Employing personal protective equipment, including helmets for safety, at industrial sites is the ultimate step in averting disasters, and such equipment is commonly recognized the disposable items. Industrial safety helmets employ Polypropylene Terephthalate (PET) or polypropylene (PP) resins is the primary material for shell to efFiciently absorb impacts. Additionally, they exhibit a commendable level of heat resistance. Nevertheless, there is currently a lack of active initiatives to develop novel materials using a straightforward fabrication approach. The objective of this work was to enhance safety behaviour of industrial helmets by using epoxy resin as the matrix to develop composite material consisting of glass Fiber and basalt Fiber in a direct cross-ply arrangement. Subsequently, the performance of this composite material was evaluated in relation to glass and basalt composites, and PET plastic. The samples are produced through compression molding method. The tensile strength (TS), Flexural strength (FS), impact strength (IS), and inter laminar shear strength (ILSS), and their heat resistance capabilities are assessed using thermo gravimetric analysis (TGA). The impact energy absorptions of BFRP, BF/GFRP, and GFRP were 6.3, 6.1, and 5.2 times higher than that of PET plastic correspondingly. Superior heat resistance was demonstrated by specimens built of Basalt Fiber Reinforced Polymer (BFRP) and Basalt Fiber/Glass Fiber Reinforced Polymer (BF/GFRP), as compared to the other scenarios. For instance, when compared to PET plastic, BFRP was 24.9 times stronger while BF/GFRP was 12.7 times stronger. The outcomes of this research work are showed that the basalt and glass Fiber reinforced composites (BF/GFRP) exhibit the superior impact energy absorption than PET plastic. © 2024 Institute of Physics Publishing. All rights reserved.

关键词： Impact strength

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mechatronics Design of Wheeled Mobile Robotic System for Gutter Maintenance 30

Mechatronics Design of Wheeled Mobile Robotic System for Gut...

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30th IEEE International Conference on Electronics, Electrical engineering and Computing, INTERCON 2023

作者： Arbulu, Mario Arias, Geyni Iniguez, Brayan Dussan, Sofia Barreto, Ricardo Cornejo, Jose CORHUILA Mechatronics Engineering Program Colombia CORHUILA Industrial Engineering Program Colombia Robotics 4.0 R and D Department Colombia Universidad Nacional de Ingeniería Center for Space Emerging Technologies Lima Peru Universidad Tecnológica Del Perú Lima Peru

ISBN: (纸本)9798350315578

This paper deals with the challenges involved on roof building gutter maintenance robot design, from the problem statement of secure teleoperated semiautonomous navigation on confined gutter spaces, and the best selection of right mechatronics brush to remove the waste on gutter surface;Two concept design have been tested: Passive Brush with Parallel locomotion (PBP), and Active Brush Axial (ABA). The results on our development are shown, as following: secure robot lifting regulation, simulation environment, HMI to teleoperate, mechatronics design. Finally, some tests on simulations and current prototypes are shown, to validate our proposal, and the conclusion that the ABA design allows to remove until 85% gutter waste, instead of PBP design;furthermore, the ABA allows independent brush rotation velocity, instead of PBP design. © 2023 IEEE.

关键词： Maintenance

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Shape-adaptive stiffness variable soft gripper using porous structure

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Journal of Institute of Control, robotics and Systems 2021年第3期27卷 238-246页

作者： Lee, Jae-Young Cho, Seong J. Seo, Yong-Sin Park, Chan-Hun Park, Dong-Il Kim, Byeung-In Kim, Hwi-Su Song, Sung-Hyuk Department of Robotics & Mechatronics Korea Institute of Machinery & Materials Daejeon Korea Republic of School of Mechanical Engineering Chungnam National University Daejeon Korea Republic of

Robotic grippers are essential components used in robots to perform certain tasks. Effective gripping capabilities are important for industrial and service robots. However, the parallel-type gripper, which is one of the most widely used robotic grippers, has limitations in terms of the objects that it can handle as well as applying the correct handling force, especially when handling fragile objects. Hence, a soft gripper fabricated using soft materials is proposed as a new alternative, with the advantage of preventing injuries when human-robot interaction is required. However, the limited holding force and uncontrollable movement of a soft gripper, due to its softness, could limit its use in real-life conditions. Therefore, in this article, we propose a shape-adaptive tip using a variable stiffness mechanism. To decrease the initial stiffness of the gripper tip, the reticulated polyurethane foam structure was embedded in the tip as the soft supporting layer to support the external force. The flexible mesh structure was applied as the jamming layer to change the stiffness of the tip. The prototype of the gripping system was tested, and the gripper could transfer the grape effectively without damage using the jamming mechanism. © ICROS 2021.

关键词： Grippers

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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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MPPI-DBaS: Safe Trajectory Optimization with Adaptive Exploration

arXiv

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arXiv 2025年

作者： Wang, Fanxin Cheng, Yikun Tao, Chuyuan Department of Mechatronics and Robotics Xi’an Jiaotong-Liverpool University China Department of Mechanical Science and Engineering University of Illinois at Urbana-Champaign United States

In trajectory optimization, Model Predictive Path Integral (MPPI) control is a sampling-based Model Predictive Control (MPC) framework that generates optimal inputs by efficiently simulating numerous trajectories. In practice, however, MPPI often struggles to guarantee safety assurance and balance efficient sampling in open spaces with the need for more extensive exploration under tight constraints. To address this challenge, we incorporate discrete barrier states (DBaS) into MPPI and propose a novel MPPI-DBaS algorithm that ensures system safety and enables adaptive exploration across diverse scenarios. We evaluate our method in simulation experiments where the vehicle navigates through closely placed obstacles. The results demonstrate that the proposed algorithm significantly outperforms standard MPPI, achieving a higher success rate and lower tracking errors. © 2025, CC BY.

关键词： Stochastic systems

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Sudden Cardiac Arrest Detection Based on Temporal Features of ECG Using Support Vector Machine Classifier

Sudden Cardiac Arrest Detection Based on Temporal Features o...

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International Conference on Industrial Instrumentation and Control,ICI2C 2021

作者： Banerjee, Prakash Bhattacherjee, Saptak Dasgupta, Kousik Department of Electrical and Electronics Engineering University of Engineering and Management Kolkata India School of Mechatronics and Robotics Indian Institute of Engineering Science and Technology Howrah Shibpur India Department of Computer Science and Engineering Kalyani Government Engineering College Kalyani India

ISBN: (纸本)9789811670107

Sudden cardiac arrest (SCA) is caused due to malfunctioning in heart rhythm, and the patient needs to be hospitalized as early as possible just after the onset of SCA;otherwise, it can lead to the death of the patient. Therefore, detection of SCA with a very high accuracy and within a very short time after the onset of symptoms is very crucial for patient survival. Several approaches for detection of SCA have been made using temporal and morphological variations in the electrocardiogram (ECG). However, the existing methods suffer from low accuracy or involve long-term monitoring of ECG. Therefore, in the present work, an intelligent algorithm to detect SCA based on the extraction of temporal features like RR interval and the QT interval from ECG and subsequently classifying them using support vector machine (SVM) has been proposed. Experimental evaluation of the proposed method on five SCA and five normal subjects demonstrates a high classification accuracy of 100% which proves the superiority of the proposed algorithm as an effective method for detection of SCA. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Electrocardiograms

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Toolpath and Tool Design Innovations in Deformation Machining for Superior AA-7075 T6 Fins 6

Toolpath and Tool Design Innovations in Deformation Machinin...

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6th International Conference on Advancements in Materials and Manufacturing, ICAAMM 2024

作者： Ponnusamy, Prasanth Seenivasan, S. Loganathan, Ganesh Babu Magesh Babu, D. Sivalingam, A. Nanthakumar, S. Girimurugan, R. Department of Mechanical Engineering Tagore Institute of Engineering and Technology Tamilnadu Salem636 112 India Department of Mechanical Engineering Rathinam Technical Campus Tamilnadu Coimbatore641 021 India Department of Robotics and Automation Rajalakshmi Engineering College Tamilnadu Chennai602 105 India Department of Mechatronics Engineering Velammal Institute of Technology Tamilnadu Panjetty601 204 India Department of Mechatronics Engineering Sona College of Technology Tamilnadu Salem636 005 India Department of Mechanical Engineering PSG Institute of Technology and Applied Research Tamilnadu Coimbatore641 062 India Department of Mechanical Engineering Nandha College of Technology Tamilnadu Perundurai638 052 India

A hybrid manufacturing process, deformation machining (DM) combines subtractive manufacturing with incremental forming. Monolithic components with complex profiles are created through the hybridization of manufacturing technologies, which also reduces the wastage of raw materials. The properties of geometry and surface quality of the fin made from the aluminum alloy Al-7075 T6 using the DM process's bending mode was examined in this research, as were the effects of various approaches, toolpath methods, and tool design. To achieve the desired shape for the machined fin, various combinations of arcuate and slanting fin toolpath techniques were explored utilizing both top-down and bottom-up methods. The bottom-up method and the arcuate toolpath strategy were used to investigate various tool profiles. Using the best combination of toolpath strategy and tool profile, named as the T3 tool profile, which has a 0.6 mm nose radius and a circular sector, bottom-to-top (BTT)technique, and arcuate toolpath method, components with better geometrical features and surface roughness (SR) were produced. The analysis of the forming force in the bending approach of the DM progression was further carried out using this optimal combination. © Published under licence by IOP Publishing Ltd.

关键词： Bending (forming)

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Iodine-enhanced Liver Vessel Segmentation in Photon Counting Detector-based Computed Tomography using Deep Learning 7

Iodine-enhanced Liver Vessel Segmentation in Photon Counting...

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7th International Conference on Image Formation in X-Ray Computed Tomography

作者： Baek, Sumin Lee, Okkyun Ye, Donghye The Department of Robotics and Mechatronics Engineering Daegu Gyeongbuk Institute of Science and Technology Daegu42988 Korea Republic of The Department of Electrical and Computer Engineering Marquette University MilwaukeeWI53233 United States

ISBN: (纸本)9781510656697

Liver vessel segmentation is important in diagnosing and treating liver diseases. Iodine-based contrast agents are typically used to improve liver vessel segmentation by enhancing vascular structure contrast. However, conventional computed tomography (CT) is still limited with low contrast due to energy-integrating detectors. Photon counting detector-based computed tomography (PCD-CT) shows the high vascular structure contrast in CT images using multi-energy information, thereby allowing accurate liver vessel segmentation. In this paper, we propose a deep learning-based liver vessel segmentation method which takes advantages of the multi-energy information from PCD-CT. We develop a 3D UNet to segment vascular structures within the liver from 4 multi-energy bin images which separates iodine contrast agents. The experimental results on simulated abdominal phantom dataset demonstrated that our proposed method for the PCD-CT outperformed the standard deep learning segmentation method with conventional CT in terms of dice overlap score and 3D vascular structure visualization. © 2022 SPIE.

关键词： Iodine

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