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Design of the Interior Permanent Magnet Synchronous Motor for Electric Vehicles Using Grain-Oriented Electrical Steel

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Transactions of the Korean Institute of Electrical Engineers 2022年第7期71卷 939-944页

作者： Kwon, Min-Su Lim, Dong-Kuk Seo, Hyeon-Uk Dept. of Electrical Electronic and Computer Engineering University of Ulsan Korea Republic of Dept. of Robotics & Mechatronics Korea Institute of Machinery Materials Korea Republic of

In this paper, the interior permanent magnet synchronous motor (IPMSM) for electric vehicles (EVs) using grain-oriented electrical steel (GO) is proposed. It was confirmed through the B-H characteristic curve and the B-W characteristic curve that the GO has superior magnetic characteristic compared to the non-grain-oriented electrical steel (NO). In order to maximize the effect of GO, the GO was partially applied to the stator teeth that has a uniform magnetic flux direction through magnetic path analysis of the EV traction motor. It has been confirmed that the output and various characteristics of the motor have improved with the application of GO. In particular, the iron loss was decreased by 44.83% in no-load condition. Moreover, the average torque and the efficiency were increased by 5.26%, 0.29%, respectively and the iron loss was decreased by 42.45% in load condition. The result of this study shows that the partial application of the GO in IPMSM improves the performance of the motor, effectively © 2022 Korean Institute of Electrical Engineers. All rights reserved.

关键词： Traction motors

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Probabilistic Modelling and Safety Assurance of an Agriculture Robot Providing Light-Treatment 19

Probabilistic Modelling and Safety Assurance of an Agricultu...

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19th IEEE International Conference on Automation Science and engineering, CASE 2023

作者： Adam, Mustafa Ye, Kangfeng Anisi, David A. Cavalcanti, Ana Woodcock, Jim Morris, Robert Robotics Group Faculty of Science & Technology Norway University of York Dept. of Computer Science United Kingdom Faculty of Engineering and Science Dept. of Mechatronics Norway Saga Robotics As Norway

ISBN: (纸本)9798350320695

Continued adoption of agricultural robots postulates the farmer's trust in the reliability, robustness and safety of the new technology. This motivates our work on safety assurance of agricultural robots, particularly their ability to detect, track and avoid obstacles and humans. This paper considers a probabilistic modelling and risk analysis framework for use in the early development phases. Starting off with hazard identification and a risk assessment matrix, the behaviour of the mobile robot platform, sensor and perception system, and any humans present are captured using three state machines. An auto-generated probabilistic model is then solved and analysed using the probabilistic model checker PRISM. The result provides unique insight into fundamental development and engineering aspects by quantifying the effect of the risk mitigation actions and risk reduction associated with distinct design concepts. These include implications of adopting a higher performance and more expensive Object Detection System or opting for a more elaborate warning system to increase human awareness. Although this paper mainly focuses on the initial concept-development phase, the proposed safety-assurance framework can also be used during implementation, and subsequent deployment and operation phases. © 2023 IEEE.

关键词： Agricultural robots

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INNOVATIVE Y-SHAPED STENT FABRICATION: A LEAP FORWARD IN BIFURCATION LESION TREATMENT

INNOVATIVE Y-SHAPED STENT FABRICATION: A LEAP FORWARD IN BIF...

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ASME 2024 International Mechanical engineering Congress and Exposition, IMECE 2024

作者： Gharaie, Saleh Zolfagharian, Ali Moghadam, Amir Ali Amiri School of Engineering Faculty of Science Engineering and Built Environment Deakin University Burwood Australia Dept. of Robotics & Mechatronics Engineering Kennesaw State University AtlantaGA United States

ISBN: (纸本)9780791888629

This study introduces a novel method for fabricating Yshaped stents from Nitinol sheets, aimed at addressing clinical needs more effectively than current braided designs. Stents play a crucial role in treating narrowed blood vessels, but conventional methods often result in high bending resistance and increased risk of in-stent restenosis (ISR). The proposed method allows for precise control over the stent's flexibility and mesh density, overcoming the limitations of braiding techniques. A complex Y-shaped stent design was developed and subjected to extensive mechanical testing, including tensile, bending, and crush resistance tests, and finite element analysis (FEA). The results demonstrated that the developed stent exhibited superior flexibility, lower bending resistance, and high structural integrity under various load conditions. The stent's performance was benchmarked against a commercially available Y-shaped stent, showing comparable or improved mechanical properties. This innovative approach enhances the mechanical performance of Yshaped stents and also opens new possibilities for design customization, potentially improving clinical outcomes and reducing complications associated with stent implantation. Copyright © 2024 by ASME.

关键词： Tensile testing

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RT-Swap: Addressing GPU Memory Bottlenecks for Real-Time Multi-DNN Inference 30

RT-Swap: Addressing GPU Memory Bottlenecks for Real-Time Mul...

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30th IEEE Real-Time and Embedded Technology and Applications Symposium, RTAS 2024

作者： Kang, Woosung Lee, Jinkyu Lee, Youngmoon Oh, Sangeun Lee, Kilho Chwa, Hoon Sung DGIST Dept. of Electrical Engineering and Computer Science Korea Republic of Dept. of Computer Science and Engineering Korea Republic of Hanyang University Dept. of Robotics Korea Republic of Ajou University Department of Software and Computer Engineering Korea Republic of School of AI Convergence Soongsil University Korea Republic of

ISBN: (纸本)9798350358414

The increasing complexity and memory demands of Deep Neural Networks (DNNs) for real-Time systems pose new significant challenges, one of which is the GPU memory capacity bottleneck, where the limited physical memory inside GPUs impedes the deployment of sophisticated DNN models. This paper presents, to the best of our knowledge, the first study of addressing the GPU memory bottleneck issues, while simultaneously ensuring the timely inference of multiple DNN tasks. We propose RT-Swap, a real-Time memory management framework, that enables transparent and efficient swap scheduling of memory objects, employing the relatively larger CPU memory to extend the available GPU memory capacity, without compromising timing guarantees. We have implemented RT-Swap on top of representative machine-learning frameworks, demonstrating its effectiveness in making significantly more DNN task sets schedulable at least 72% over existing approaches even when the task sets demand up to 96.2% more memory than the GPU's physical capacity. © 2024 IEEE.

关键词： Deep neural networks

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Implicit Grasp Diffusion: Bridging the Gap between Dense Prediction and Sampling-based Grasping 8

Implicit Grasp Diffusion: Bridging the Gap between Dense Pre...

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8th Conference on Robot Learning, CoRL 2024

作者： Song, Pinhao Li, Pengteng Detry, Renaud KU Leuven Dept. Mechanical Engineering Research Unit Robotics Automation and Mechatronics Belgium KU Leuven Dept. Electrical Engineering Research Unit Processing Speech and Images Belgium AI Thrust Hong Kong

There are two dominant approaches in modern robot grasp planning: dense prediction and sampling-based methods. Dense prediction calculates viable grasps across the robot's view but is limited to predicting a fixed number of grasps per voxel. Sampling-based methods, on the other hand, encode multi-modal grasp distributions, allowing for different grasp approaches at a point. However, these methods rely on a global latent representation, which struggles to represent the entire field of view, resulting in coarse grasps. To address this, we introduce Implicit Grasp Diffusion (IGD), which combines the strengths of both methods by using implicit neural representations to extract detailed local features and sampling grasps from diffusion models conditioned on these features. Evaluations on clutter removal tasks in both simulated and real-world environments show that IGD delivers high accuracy, noise resilience, and multi-modal grasp pose capabilities. Our code is freely available at https://***/detry-lab/public/***. © 2024 Proceedings of Machine Learning Research.

关键词： Robot programming

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Advancing Pedestrian Attribute Classification: A Multi-Head Deep Learning Paradigm 12

Advancing Pedestrian Attribute Classification: A Multi-Head ...

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2024 12th International Conference on Systems and Control, ICSC 2024

作者： Bekbolat, Amanali Kurokawa, Syuhei Tanveer, Muhammad Hassan Ali, Md. Hazrat Nazarbayev University SEDS Dept. of Mechanical and Aerospace Engineering Astana Kazakhstan Kyushu University Dept. of Mechanical Engineering Nishi-ku Fukuoka819-0395 Japan Kennesaw State University Dept. of Robotics and Mechatronics Engineering MariettaGA30067 United States

ISBN: (纸本)9798331531812

Evaluating pedestrians is critical when designing new systems for more sophisticated video monitoring and innovative computer vision-based security. Although convolutional neural networks successfully learn different features from images, modeling the pedestrians to the details needed for such tasks remains an issue. In this paper, we present a novel approach based on the multi-head deep learning model to identify the pedestrian attributes, which has merits in this method. Thus, the proposed approach yields better accuracy, robustness, and efficiency in comparison to state-of-the-art methods on a novel database consisting of pedestrian images. We also incorporate further pre-processing steps whereby data augmentation, transfer learning, and model ensembling are additional methods that are used to improve the generality and applicability of the approach proposed in this study. This framework empirically achieves promising accuracy and outperforms existing approaches, proving the usefulness and robustness of our idea in terms of pedestrian attribute recognition. © 2024 IEEE.

关键词： Contrastive Learning

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Independent Optimization for Robot Path Planning and Dynamic Obstacle Avoidance 19

Independent Optimization for Robot Path Planning and Dynamic...

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19th IEEE International Conference on Smart Communities: Improving Quality of Life Using ICT, IoT and AI, HONET 2022

作者： Hall, Terrance Johnson, Christopher Swales, Brighton Koduru, Charles Tanveer, M. Hassan Kennesaw State University Dept. of Robotics and Mechatronics Engineering Marietta United States

ISBN: (纸本)9781665461979

Autonomous robots can be assigned with various tasks such as moving payload, analyzing terrain, and capturing data in an environment. For an Autonomous Mobile Robot (AMR) to execute such tasks the robot (Hussarion ROSbot) will require efficient algorithms and techniques to reference its current location. The robot is relative to surrounding obstacles in its predetermined path. The conducted research study explains the coordinated method used to successfully allow a robot to identify its position in the environment (Gazebo Simulation) and avoid obstructions with increasing velocity - contingent on nearby surroundings. The results show multiple robots individually tasked with distinct roles, while incorporating an obstacle avoidance function used to avoid both static and dynamic obstacles. Such results can be used in the applications of a high-capacity warehouse environments. © 2022 IEEE.

关键词： Multipurpose robots

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Design and Analysis of a Novel Hybrid Grasping Mode Microgripper for High Precision Tasks 9

Design and Analysis of a Novel Hybrid Grasping Mode Microgri...

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9th IEEE International Women in engineering (WIE) Conference on Electrical and Computer engineering, WIECON-ECE 2023

作者： Das, Tilok Kumar Shahrear, Rifat Das, Arpita Shirinzadeh, Bijan Dept. of Mechanical Engineering Chattogram Bangladesh Temple University Dept. of Electrical and Computer Engineering PhiladelphiaPA United States Monash University Robotics and Mechatronics Research Laboratory Dept. of Mechanical and Aerospace Engineering MelbourneVIC Australia

ISBN: (纸本)9798350319651

This paper represents a novel piezoelectric actuated flexure-based compliant microgripper which can perform both parallel and angular grasping regardless of the geometric surface of the objects. Two compliant bridge-type mechanisms along with two symmetrical microgripper jaws at the end of the two side arms are accommodated to construct the microgripper. The two side arms of the microgripper act as lever-type amplification mechanisms. Simultaneous actuation of two bridge-type mechanisms is needed to perform linearized parallel grasping. The symmetric design is adopted to maintain better stability. The Finite Element Analysis (FEA) has been performed to evaluate the performance of the microgripper. FEA shows that each jaw of the microgripper can achieve a displacement of 141.72 μm resulting in a total displacement of 283.44 μm with an amplification ratio of 10.7 and 0.715% parasitic motion in y-direction of the X -axis displacement during parallel grasping. Also, each jaw can achieve a displacement of 283.88 μm which results in a total displacement of 567.76 μm with an amplification ratio of 21.5 and 5.17 mrad angular rotation about the Z-axis during angular grasping. The FEA suggests that the microgripper is capable of both parallel and angular grasping/releasing tasks. © 2023 IEEE.

关键词： Piezoelectric actuators

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Development of Smart Orthosis with Real-time Corrective Feedback 17

Development of Smart Orthosis with Real-time Corrective Feed...

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17th International Conference on engineering of Modern Electric Systems, EMES 2023

作者： Oarcea, Alexandru Popister, Florin Ciudin, Paul Salatioan, Michael Christian The Politechnic University of Timisoaora Dept. of Mechatronics Timisoara Romania Technical University of Cluj-Napoca Dep. of Design Engineering and Robotics Cluj-Napoca Romania

ISBN: (纸本)9798350310634

In this paper we analyze the development process of a smart knee orthosis that can monitor the bearer's movements and provide real-time feedback to aid the bearer's proper recovery after an injury. The development process includes the 3D scanning of the patients knee joint, the 3D modeling of the orthosis, the 3D printing of the orthosis, the integration of IMU (Inertial Measurement Unit) sensors, the integration of the microcontroller and the implementation of the data acquisition and control. The implementation with the use of 3D printing parts will guarantee the best fit on the wearer's foot, offering increased comfort. © 2023 IEEE.

关键词： Microcontrollers

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FFT-UAVNet: FFT Based Human Action Recognition for Drone Surveillance System

FFT-UAVNet: FFT Based Human Action Recognition for Drone Sur...

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Sustainable Technologies for Industry 4.0 (STI), International Conference on

作者： Abdul Monaf Chowdhury Ahsan Imran Md Mehedi Hasan Dept. of Robotics and Mechatronics Engineering University of Dhaka Bangladesh

Unmanned aerial vehicles (UAVs) have emerged as a transformative technology for human action recognition, providing a birds-eye view and unlocking new possibilities for precise and comprehensive support in surveillance systems. While substantial advances in ground-based human action recognition have been achieved, the unique characteristics of UAV footage present new challenges that require tailored solutions. Specifically, the reduced scale of humans in aerial perspectives necessitates the development of specialised models to accurately recognize and interpret human actions. Our research focuses on modifying the well-established C3D model and incorporating Fast Fourier Transform (FFT)-based object disentanglement (FO) and space-time attention (FA) mechanisms. By leveraging the power of FFT, our model effectively disentangles the human actors from the background and captures the spatio-temporal dynamics of human actions in UAV footage, enhancing the discriminative capabilities and enabling accurate action recognition. Through extensive experimentation on a subset of the UAV-Human dataset, our proposed FFT-UAVNet (m-C3D+FO&FA+FC) model demonstrates remarkable improvements in performance. We achieve a Top-1 accuracy of 64.86% and a Top-3 accuracy of 83.37%, surpassing the results obtained by the standard C3D and X3D methods, which achieve only a Top-1 accuracy of 28.05% and 31.33%, respectively. These findings underscore the efficacy of our approach and emphasize the significance of the proposed model for UAV datasets in maximizing the potential of UAV-based human action recognition.

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