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2023 IEEE International Conference on Real-Time Computing and robotics, RCAR 2023

作者： Jiang, Jialin Yang, Lidong Zhang, Li The Chinese University of HongKong Department of Mechanical and Automation Engineering Hong Kong Hong Kong Department of Industrial and Systems Engineering China The Chinese University of Hong Kong Department of Surgery Hong Kong The Chinese University of Hong Kong Cuhk T Stone Robotics Institute Hong Kong Hong Kong The Chinese University of Hong Kong Chow Yuk Ho Technology Center for Innovative Medicine Hong Kong Hong Kong Science Park Multi-Scale Medical Robotics Center China

ISBN: (纸本)9798350327182

Untethered microrobots possess a promising perspective for micro-manipulation applications. With specifically designed morphologies and structures, microrobots are able to perform controllable delivery of target objects. However, the manipulation process still lacks autonomy, the picking, transporting, and releasing behaviors of microrobots need analysis. In this paper, we propose to achieve automated microrobotic manipulation with multimodal magnetic microswarms. The microswarm is composed of numerous Fe3O4 nanoparticles. When exposed to different dynamic magnetic fields (rotating magnetic field and oscillating magnetic field), the swarm could exhibit corresponding forms and generate attracting and repelling effects for micro-objects, respectively. Exploiting these two types of swarms, precise and controllable picking and releasing can be realized. The manipulation process is quantitatively divided into five stages, and a finite state machine (FSM) is presented to govern the transition between the stages. To guarantee accurate motion control of the swarm, a disturbance observer (DOB)-based super-twisting sliding mode control (STSMC) is designed. Experiments are conducted to validate the feasibility of the proposed manipulation scheme. The results demonstrate that the swarm is capable of automatically and effectively delivering micro-cargoes with different sizes to the target positions. © 2023 IEEE.

关键词： Magnetite

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A Novel Equilibrium Optimization Algorithm for Optimal Coordination of Directional Overcurrent Relays 1

A Novel Equilibrium Optimization Algorithm for Optimal Coord...

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1st International Conference on engineering and Advanced Technology, ICEEAT 2023

作者： Djamel, Mohammedi Ridha Mustafa, Mosbah Rabie, Zine Abdelouahab, Khattara Sidi, Maawiya Ould Soufi, Yousef Ziane Achour University Applied Automation and Industrial Diagnostics Laboratory Djelfa Algeria Amar Telidji University Laghouat and University of Ghardaia LACoSERE Laboratory Department of Electrical Engineering Algeria Al Akhawayn University in Ifrane School of Science and Engineering Morocco Ghardaia University Energy Systems Modeling Laboratory Ghardaia Algeria Jouf University RT-M2A Laboratory Mathematics Department College of Science Sakaka Saudi Arabia Larbi Tebessi University Electrical Engineering Department Tebessa Algeria

ISBN: (纸本)9798350383485

Short circuit protection is considered an important task to provide reliability and correct performance of power system. For this reason, it is necessary to have a good choice of settings of various settings of current directional relay, in order to assure the effectiveness of tripping of protection device. The objective of this work is to optimize of Coordination of Directional Overcurrent Relays (This is achieved by optimizing the parameters Time-Dial Setting-or TDS and Pickup Current Setting-OR PCS). The optimization method used is new metaheuristic based on a newly proposed optimization technique, namely the Equilibrium Optimization (EO) algorithm. The goal of this study is to minimize the total operation time of all primary relays required to eliminate faults within their respective regions. This study was realized on IEEE 4-bus, 8-bus, and 15-bus networks under MATLAB2023a. The obtained results are compared with similar works in the literature. Results obtained demonstrate the efficacy of the proposed approach towards the minimization of the relay running time for an optimal coordination of Directional Overcurrent Relays (DOCRs). © 2023 IEEE.

关键词： Optimization

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Automating CPPSs Analyses with SysML v2 and Lingua Franca in the Context of Industry 4.0

Automating CPPSs Analyses with SysML v2 and Lingua Franca in...

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Annual Conference of industrial Electronics Society

作者： Sebastiano Gaiardelli Jan Wilch Franco Fummi Birgit Vogel-Heuser Department of Engineering for Innovation Medicine Industrial Computer Engineering Laboratory University of Verona Italy Institute of Automation and Information Systems Technical University of Munich Germany Institute of Automation and Information Systems Core Member of MDSI Member of MIRMI Technical University of Munich Germany

ISBN: (数字)9781665464543

ISBN: (纸本)9781665464550

The design of manufacturing systems requires exploring diverse component configurations for one that best satisfies the requirements of the target system. At the same time, manufacturing systems evolve continuously, increasing their complexity and that of the production line in which they are installed. Model-based System engineering (MBSE) methodologies and modeling languages like System Modeling Language (SysML) are used to assist system engineers during the entire design process. Yet, MBSE methodologies mainly rely on manually composed models for requirements verification, incurring enormous cost and effort especially in larger, more complex systems. This paper proposes a methodology exploiting the knowledge enclosed in a SysML model to automate the execution of a set of analyses defined over the represented manufacturing system. The proposed approach relies on Lingua Franca (LF) to simulate the specified analysis and analyze the results. Moreover, the methodology supports chains of analyses to represent dependent requirements and tradeoffs imposed upon a manufacturing system. The proposed methodology has been evaluated on a manufacturing system demonstrator. Results show the proposed methodology's applicability and scalability on diverse configurations of the manufacturing system.

关键词： industrial electronics Analytical models Translation Costs Scalability Production systems Modeling Language Libraries Fourth industrial Revolution Manufacturing systems

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Digital Twin Definition for Detecting Abnormal Perspiration Patterns in High-Stress Professions 23

Digital Twin Definition for Detecting Abnormal Perspiration ...

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23rd RoEduNet Conference: Networking in Education and Research, RoEduNet 2024

作者： Vizitiu, Cristian Turcin, Ioan Dominey, Kevin Alexander Softic, Selver Dinculescu, Adrian-Catalin Bocanet, Vlad I. Dugan, Cosmin Moraru, Sorin-Aurel The Space Applications and Technologies Laboratory Institute of Space Science-Subsidiary of INFLPR Magurele Romania Transilvania University of Brasov Faculty of Electrical Engineering and Computer Science Department of Automatics and Information Technology Brasov Romania CAMPUS 02 University of Applied Sciences Department Automation Technology Graz Austria CAMPUS 02 University of Applied Sciences Department IT and Business Informatics Graz Austria Robotics and Production Management Technical University of Cluj-Napoca Cluj-Napoca Faculty of Industrial Engineering Department of Manufacturing Engineering Romania Bucharest University Emergency Hospital Bucharest Romania

ISBN: (纸本)9798331540388

Perspiration is a physiological response in high-stress situations, that also plays a key role in thermoregulation and stress management. Understanding perspiration patterns is used for assessing physiological responses and optimizing human performance especially in professions such as emergency medical services and military operations, as well as for individuals exposed to Isolated Confined Extreme (ICE) environments such as astronauts and space analog mission participants. This paper defines a Digital Twin (DT) model, that will be integrated with an existing physical sweat simulator module (SSM) prototype. Its goal is to simulate human perspiration under high-stress conditions by integrating environmental, physiological, and psychological data. The system architecture is developed via Model-Based systems engineering (MBSE). The scope of the designed virtual model is to accurately reflect physical perspiration, detect abnormal perspiration patterns, and generate recommendations regarding stress countermeasures. The goal is to influence the behavioral and/or physiological state of the physical twin, thereby creating a dynamic, responsive system. Machine learning (ML) models will be used to identify patterns in the environmental, physiological, and psychological inputs and predict sweat volume, chemical composition, and regional sweat distributions across the body. ML will also be used to detect abnormal perspiration patterns based on input data. The application of generative AI for creating test data from simulation templates is anticipated to facilitate the comparative analysis of two to three distinct profiles, such as astronauts, soldiers, and paramedics or firefighters, using simulated values. The SSM, with its integrated sensors, will serve the dual purpose of validating the model and providing realistic physical simulation. © 2024 IEEE.

关键词： Physiological models

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A Modified Artificial Potential Field Method Based on Subgoal Points for Mobile Robot 16th

A Modified Artificial Potential Field Method Based on Subgoa...

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16th International Conference on Intelligent robotics and Applications, ICIRA 2023

作者： Mo, Jixue Gao, Changqing Liu, Fei Yang, Qingkai Fang, Hao Department of Mathematics and Theories Pengcheng Laboratory Shenzhen518055 China School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen518055 China Industrial Training Center Shenzhen Polytechnic Shenzhen518055 China Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing100081 China

ISBN: (纸本)9789819964826

In this paper, a modified artificial potential field (MAPF) method was proposed for general mobile robot navigation system. This MAPF method can effectively solve the unreachable goal problem and the local minima problem of traditional APF method. The first key idea of MAPF method is to modify the repulsive force function and thus optimize the direction of total repulsive force;the second key idea is to generate a serials of subgoal points around obstacles with specific method, so as to help the robot escape from or keep away from local minima area. By comparing with other similar algorithms in simulation environment, the MAPF algorithm can generate shorter paths efficiently. More importantly, it also can generate effective paths in multi-obstacle environment where other algorithms cannot. Finally the simulation results verified the reasonability and practicability of the proposed MAPF method. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Motion planning

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Design of magnetorheological brake with adjustable interdigitated comb for lower limb prostheses and exoskeletons

Design of magnetorheological brake with adjustable interdigi...

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2023 IEEE International Conference on robotics and Biomimetics, ROBIO 2023

作者： Shi, Qiuyu Zhao, Xuan Liao, Haisu Lin, Yongji Huang, Ruisen Wu, Xinyu Gao, Fei Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen518055 China Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen518055 China The Chinese University of Hong Kong Department of Mechanical and Automation Engineering Shatin 999077 Hong Kong

ISBN: (纸本)9798350325706

Magnetorheological (MR) fluids-based devices such as MR dampers and brakes can output a continuously controllable damping force via modulating the magnitude of the applied magnetic field. Owing to low energy consumption and fast response, recently vast MR dampers and brakes are widely studied and explored for lower limb prostheses and exoskeletons. This paper proposed a novel MR brake with adjustable interdigitated comb for lower limb prostheses. Through actively adjusting the area the of the comb engagement, the maximum viscous and field-induced damping torque can be increased or decreased. Because of that, the dynamic adjustment interval of the output damping torque can be increased to meet the function requirements of the prosthetic knee in different walking modes. Magnetic analysis via ANSYS is performed to check the magnetic density of the MR fluid under different excitations. Mathematical models of the damping torque are built. Finally, a prototype of the novel MR brake is fabricated. © 2023 IEEE.

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Diffusion-Based mmWave Radar Point Cloud Enhancement Driven by Range Images

arXiv

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arXiv 2025年

作者： Wu, Ruixin Li, Zihan Wang, Jin Xu, Xiangyu Yu, Huan Zheng, Zhi Huang, Kaixiang Lu, Guodong The State Key Laboratory of Fluid Power and Mechatronic Systems School of Mechanical Engineering Zhejiang University Hangzhou310058 China Zhejiang Key Laboratory of Industrial Big Data and Robot Intelligent Systems Zhejiang University Hangzhou310058 China Robotics Research Center of Yuyao City Ningbo315400 China State Key Laboratory of Robotics and Systems Department of Mechatronics Engineering Harbin Institute of Technology Harbin150001 China

Millimeter-wave (mmWave) radar has attracted significant attention in robotics and autonomous driving. However, despite the perception stability in harsh environments, the point cloud generated by mmWave radar is relatively sparse while containing significant noise, which limits its further development. Traditional mmWave radar enhancement approaches often struggle to leverage the effectiveness of diffusion models in super-resolution, largely due to the unnatural range-azimuth heatmap (RAH) or bird’s eye view (BEV) representation. To overcome this limitation, we propose a novel method that pioneers the application of fusing range images with image diffusion models, achieving accurate and dense mmWave radar point clouds that are similar to LiDAR. Benefitting from the projection that aligns with human observation, the range image representation of mmWave radar is close to natural images, allowing the knowledge from pre-trained image diffusion models to be effectively transferred, significantly improving the overall performance. Extensive evaluations on both public datasets and self-constructed datasets demonstrate that our approach provides substantial improvements, establishing a new state-of-the-art performance in generating truly three-dimensional LiDAR-like point clouds via mmWave radar. Copyright © 2025, The Authors. All rights reserved.

关键词： Radar imaging

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Upconversion Pumped Tm3+:KY3F10 Channeled Waveguide Laser at 2.3 μm and 1.9 μm

Upconversion Pumped Tm3+:KY3F10 Channeled Waveguide Laser at...

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2024 Advanced Solid State Lasers, ASSL 2024

作者： Ince, Faik Derya Morova, Yagiz Tonelli, Mauro Sennaroglu, Alphan Laser Research Laboratory Departments of Physics and Electrical-Electronics Engineering Koç University Istanbul34450 Turkey Department of Industrial & Systems Engineering Manufacturing and Automation Research Laboratory Rutgers University New BrunswickNJ United States Rumelifeneri Istanbul34450 Turkey MEGAMATERIALS s.r.l and Dipartimento di Fisica dell'Università di Pisa Largo B.Pontecorvo 3 Pisa56127 Italy

We demonstrate, for the first time, a femtosecond laser written Tm3+:KY3F10 waveguide laser at 2.3 μm in continuous-wave regime and at 1.9 µm in continuous-wave and passively Q-switched regimes by upconversion p... 详细信息

关键词： Femtosecond lasers

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Towards Autonomous Robotic Ultrasound Scanning Using the Reinforcement Learning-Based Volumetric Data Navigation Method 5

Towards Autonomous Robotic Ultrasound Scanning Using the Rei...

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5th World Robot Conference Symposium on Advanced robotics and automation, WRC SARA 2023

作者： Shen, Cuifeng Deng, Zhaokun Wang, Jinzhi Wang, Shuangyi Chen, Chen Peking University State Key Laboratory for Turbulence and Complex Systems Department of Mechanics and Engineering Science College of Engineering Beijing100871 China University of Chinese Academy of Sciences School of Artificial Intelligence Beijing China Institute of Automation Chinese Academy of Sciences State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing China Hong Kong Institute of Science & Innovation Chinese Academy of Sciences Centre for Artificial Intelligence and Robotics Hong Kong

ISBN: (纸本)9798350307320

Ultrasound scanning is an indispensable diagnostic tool in modern medicine, but obtaining an accurate standard plane relies heavily on the sonographer's skill and expertise. This paper presents a novel approach toward autonomous robotic ultrasound scanning using a reinforcement learning-based navigation method with volumetric ultrasound data. The proposed method enables an ultrasound robot to autonomously acquire high-quality 2D standard planes from patients, thereby reducing the need for human intervention. The core of the approach is a deep reinforcement learning algorithm that detects 2D standard planes within the 3D ultrasound volume and guides the ultrasound probe to extract high-quality standard planes. To assess the effectiveness of the 2D standard plane detection method, an evaluation was conducted using a realworld ultrasound dataset, and a comparison was made between its performance and that of other state-of-the-art autonomous approaches. The simulation experiment was also conducted to validate the autonomous robotic ultrasound acquisition workflow. Results demonstrate that the reinforcement learning-based volumetric data navigation method outperforms existing techniques in terms of standard plane accuracy and is very effective for volumetric data-based robotic navigation. © 2023 IEEE.

关键词： Diagnosis

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Spiking neural networks: Towards bio-inspired multimodal perception in robotics

arXiv

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arXiv 2024年

作者： Oikonomou, Katerina Maria Balaska, Vasiliki Tsintotas, Konstantinos A. Mavridis, Christos N. Kansizoglou, Ioannis Gasteratos, Antonios The Department of Production and Management Engineering Laboratory of Robotics and Automation Democritus University of Thrace Xanthi Greece The Department of Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden

Spiking neural networks (SNNs) have captured apparent interest over the recent years, stemming from neuroscience and reaching the field of artificial intelligence. However, due to their nature SNNs remain far behind in achieving the exceptional performance of deep neural networks (DNNs). As a result, many scholars are exploring ways to enhance SNNs by using learning techniques from DNNs. While this approach has been proven to achieve considerable improvements in SNN performance, we propose another perspective: enhancing the biological plausibility of the models to leverage the advantages of SNNs fully. Our approach aims to propose a brain-like combination of audio-visual signal processing for recognition tasks, intended to succeed in more bio-plausible human-robot interaction applications. © 2024, CC BY-NC-SA.

关键词： Adversarial machine learning

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