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检索条件"任意字段=Proceedings of the 2020 2nd International Conference on Robotics Systems and Vehicle Technology"

共 1003 条记录，以下是181-190 订阅

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Power Optimization Control with Tracking Differentiator for Interior Permanent-Magnet Synchronous Motor 2nd

Power Optimization Control with Tracking Differentiator for ...

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conference proceedings of 2022 2nd international Joint conference on Energy, Electrical and Power Engineering

作者： Zuo, Kunkun He, Long Wang, Fengxiang Kennel, Ralpha Heldwein, Marcelo Lobo Chair of High-Power Converter Systems TUM School of Engineering Design Technical University of Munich Munich80333 Germany Quanzhou Institute of Equipment Manufacturing Haixi Institutes Chinese Academy of Sciences Quanzhou362200 China

ISBN: (纸本)9789819943333

A simple but effective power optimization control (POC) algorithm is one of the consistently pursued objectives in drive systems. However, it is still challenging to get the desired algorithm and control quality due to complicated relations between loss power and stator current. This paper proposes a power optimization strategy to achieve higher power efficiency with a more straightforward controller. Based on the mathematical characteristics of loss power, maximum torque per ampere (MTPA) and loss minimization control (LMC) methods can be both transformed into minimum problems. Then, the derivative of a given signal is extracted by using the tracking differentiator, and an adaptive optimization algorithm is tailored to converge on the optimal point quickly. The critical advantages of the proposed method are that it avoids the need for accurate motor parameters and utilizes the derivative of stator current to structure an intuitive optimization strategy. The comparative experimental results demonstrate that the proposed method achieves higher performance under different operations. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Quality control

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Control system for a robotic system for rehabilitation of lower limbs with feedback on the patient's effort 2022

Control system for a robotic system for rehabilitation of lo...

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2nd international conference on robotics and Control Engineering, RobCE 2022

作者： Rybak, Larisa Khalapyan, Sergey Rashoyan, Gagik Mohan, Santhakumar Nozdracheva, Anna Research Institute Robotics and Control Systems Bstu Named after V. G. Shukhov Belgorod Russia Stary Oskol Technological Institute N. A. A. A. Ugarov Nust MISiS Stary Oskol Belgorod Russia Mechanical Engineering Research Institute of the Russian Academy of Sciences Moscow Russia Indian Institute of Technology Palakkad Palakkad India Gamaleya National Research Center for Epidemiology and Microbiology Moscow Russia

ISBN: (纸本)9781450395854

The paper presents structural diagrams of the control system of a robotic system with feedback on the patient's effort and without it, illustrates the conditions for using each of them;a method is prepared to increase the reliability of data on the applied efforts, associated with the use of strain gauges in the absence of actions of the patient's motor organs;an example of the patient's motivation to perform "correct"movements, "helping"the mechanism, consisting in changing the speed of movement to form the patient's feeling that the mechanism moves due to his efforts;a mathematical model of the robotic system was obtained, graphs were constructed demonstrating the accuracy of working out a given trajectory due to the anthropometric parameters of the patient. © 2022 ACM.

关键词： Feedback

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Research on obstacle avoidance planning of explosion-proof AGV unmanned factory

Research on obstacle avoidance planning of explosion-proof A...

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Signal Processing and Intelligent Computing (SPIC), international conference on

作者： Bo Liu Hongwei Gao Yueqiu Jiang Jiaxuan Wu Zhen Sun Shenyang Ligong University Shenyang China Liaoshen Industry Co. LTD Shenyang China

ISBN: (数字)9798350368888

ISBN: (纸本)9798350368895

Explosion-proof AGV has gained increasing attention for meeting the demands of "man-machine isolation, machine replacement, and black light factory". Although widely utilized in unmanned factories for tasks such as transportation and workpiece handling, the dynamic nature of transportation processes, characterized by obstacles and path alterations, necessitates real-time path updates to ensure the smooth operation of AGV vehicles. This paper introduces the fundamental principles of the A* algorithm and proposes an enhanced version to address these challenges. Through simulations and experiments, various obstacle avoidance algorithms based on A* are demonstrated to be both feasible and effective.

关键词： Heuristic algorithms Signal processing algorithms Transportation Signal processing Real-time systems Production facilities Path planning Safety vehicle dynamics Collision avoidance

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Partial Discharge Detection Method for Distribution Network Based on Feature Engineering 2

Partial Discharge Detection Method for Distribution Network ...

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2nd international conference on robotics, Automation and Intelligent Control, ICRAIC 2022

作者： Liu, Hongxiao Xiang, Mian Xiang Zhou, Bingtao Zhu, Li Duan, Yaqiong Zhang, Xiaoyan College of Intelligent Systems Science and Engineering Hubei Minzu University Hubei Enshi China

Partial discharge phenomenon of overhead lines in distribution network is usually caused by the concentration of local electric field inside or on the surface of electrical equipment. According to partial discharge problem, based on the characteristics of the project the use of a machine learning is proposed for distribution network overhead line partial discharge detection model, first using the characteristics of engineering to extract the signal characteristics of different sides characterization, then respectively using K neighbor algorithm and back propagation algorithm, support vector machine (SVM) classification algorithm test. Experimental results show that when machine learning algorithm is used to classify time domain characteristic signals based on the feature engineering selected in this paper, k-nearest Neighbor algorithm has better classification and recognition effect than back propagation algorithm and support vector machine algorithm, with accuracy rate of 97.20%, recall rate of 96.30% and F value of 96.73%. In the frequency domain feature recognition and classification, the k-nearest Neighbor algorithm has 98.95% accuracy, 99.42% recall rate and 97.61% F value. Compared with the back propagation algorithm and support vector machine algorithm, the K-nearest Neighbor algorithm has the highest detection accuracy in the frequency domain feature detection of partial discharge on overhead lines of distribution network. © Published under licence by IOP Publishing Ltd.

关键词： Frequency domain analysis

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Emergence of perceptual states in mosquitoes using virtually perceived spatial cognitive abilities: Solution for Complex Problems 2

Emergence of perceptual states in mosquitoes using virtually...

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2nd international conference on Intelligent Engineering and Management, ICIEM 2021

作者： Sodhi, Prabhjyot Singh University of California San DiegoCA United States

ISBN: (纸本)9781665414500

Perceptual learning (PL) - experience-induced improvements in how people interpret and retrieve information - seems to play a bigger role in diverse cognitive functions, including abstract and conceptual domains, than previously assumed. While many nonhuman animals have their own forms of technology, such as mosquitoes who create and use tools, in environments the opportunity to actively participate with interactive technology is not often made available. When interactive technology is available, mosquitoes often selectively choose to engage with it. This enhances the mosquito's sense of control over their immediate surroundings. Our study proposed research questions and hypothesis to identify how insect cognitive system with fewer neurons and vertebrate brains can be a model system for research on Artificial Intelligence, robotics and Machine learning, since Internet of Things devices also have limited processing and low storage. © 2021 IEEE.

关键词： Cognitive systems

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A novel electrical muscle stimulation device for neurorehabilitation applications with adaptable parameter optimization using AI algorithms 12

A novel electrical muscle stimulation device for neurorehabi...

引用

12th international conference on Modern Circuits and systems Technologies, MOCAST 2023

作者： Arsenidis, Arsenios Moraitopoulos, Alexandros Athanasiou, Alkinoos Bamidis, Panagiotis Stefaneas, Petros Astaras, Alexander NTUA School of Applied Mathematical and Physical Sciences Department of Physics Athens Greece AUTH Medical Physics and Digital Innovation Laboratory School of Medicine Thessaloniki54636 Greece American College of Thessaloniki Computer Science Division of Science & Technology Thessaloniki Greece

ISBN: (纸本)9798350321074

The application of short trains of electric pulses, of appropriate frequency and power, to muscle or nerve tissue can induce action potentials which in turn lead to muscle contractions. Timing these action potentials appropriately can help enhance functional movements, a methodology called Functional Electrical Stimulation (FES). The motor and sensory recruitment of muscle and nerves by means of FES has been demonstrated to elicit short- and long-term neurophysiological changes in the central nervous system and thus constitutes a powerful therapeutic rehabilitation tool. The most significant signal parameters affecting the quality of muscle contraction and duration of cortical reorganization caused by Functional Electrical Stimulation Therapy (FEST) are pulse intensity (amplitude), frequency, pulse width and the time delay between pulses. While these parameters are particular to the stimulating signal waveform, there are other key factors at play which determine both the duration and quality of changes. Such factors are electrode placement and synchronization of voluntary command with the induced contraction, which partially determine the successful completion of a movement task. The work presented in this paper aims to study, calibrate, automate and optimize the adaptation process of the aforementioned FEST parameters with respect to induced muscle contraction intensity and perceived discomfort reported by the subject, using both conventional AI and machine learning methodologies. © 2023 IEEE.

关键词： Muscle

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Research on the Application of Deep Learning Algorithm in Visual Perception and Recognition of Artificial Intelligence Robot

Research on the Application of Deep Learning Algorithm in Vi...

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Electrical, Automation and Computer Engineering (ICEACE), international conference on

作者： Yujia Li Siheng Ren Na Yang School of Metallurgy Northeastern University Shenyang China Space Engineering University Beijing China

ISBN: (数字)9798350368208

ISBN: (纸本)9798350368215

With the rapid advancement of science and technology, artificial intelligence (AI) has emerged as a focal point in the realm of technology. Among its core branches, deep learning endows computers with formidable data processing capabilities by emulating the cognitive processes of the human brain. This work delves into the application of deep learning in robotic visual perception, encompassing areas such as image recognition, object detection, and motion planning, thereby illustrating how deep learning algorithms can markedly enhance a robot’s visual perception capabilities. To validate these enhancements, the YOLOv5 model was employed for real-time object detection, which was further integrated with the A* algorithm for robotic path planning. The outcomes demonstrate that the YOLOv5-based object detection algorithm performs admirably in complex environments. Collectively, this research furnishes fresh perspectives and methodologies for the progression of robotics technology in the future.

关键词： Deep learning YOLO Computers Heuristic algorithms Computational modeling Real-time systems Path planning vehicle dynamics Robots Visual perception

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Robot Path Planning using Modified Genetic Algorithm in EC2 2

Robot Path Planning using Modified Genetic Algorithm in EC2

引用

2nd international conference on Electronics and Sustainable Communication systems, ICESC 2021

作者： Gupta, Shivani Sharma, Kaushlendra Doriya, Rajesh NIT Department of Information Technology Raipur India

ISBN: (纸本)9781665428675

Path planning is one of the classical problem in the study of network technology in computer science, communications and operations research, geographic information system and robotics. As cloud is very popular in recent years and many organizations are switching to the cloud. This paper proposes the modified genetic algorithm to solve the problem of Robot path planning using EC2. The main purpose of path optimization is to determine the shortest path between the source node and the destination node. The proposed approach determines the shortest path using the fitness function proposed for the Genetic algorithm to perform collision free traversing of robots from its source to destination. The over all problem is solved using cloud computing platform. Here, this paper presents the concept of EC2. To validate the proposed work path length is taken as one of the important parameter. The results are comparatively better than the other relevant work and the same is validated and presented in this paper. © 2021 IEEE.

关键词： Genetic algorithms

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Prototyping and Conceptualizing Electric Model vehicles to Enhance Automotive STEM Education: Towards Sustainable E-Mobility

Prototyping and Conceptualizing Electric Model Vehicles to E...

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Education conference (GeCon), IEEE German

作者： Mbadiwe S. Benyeogor Abubakar. A. Dahiru Andrew O. Benyeogor Oladayo O. Olakanmi Akintayo Akintola Baki Adeiza Sodiq Institute of Physics University of Münster Münster Germany Abuja - FCT National Information Technology Development Agency (NITDA) Nigeria CTE - Computer Science & Robotics Lab. International Leadership of Texas Aggieland Texas USA Dept. of Electrical & Electronic Engineering University of Ibadan Ibadan Nigeria Ralph Alabi Engineering Centre Nigeria Society of Engineers (NSE) Lagos Nigeria Dept. of Vocational & Technical Education University of Benin Benin City Nigeria

Considering the rapid technological advances in the automotive industry and the trend toward electric vehicles, there is an apparent need to modify and simplify the design and prototyping of electric model vehicle systems, in order to enhance their usability in schools for demonstrating and teaching automotive engineering and other related science, technology, engineering, and mathematics (STEM) concepts. Therefore, this paper proposes an easy-to-prototype template of an educational model vehicle to teach automotive-related STEM subjects, covering automechanics, autotronics, and coding. The model vehicle is portable and affordable, making it a useful tool for teaching basic principles, design, and construction of automotive systems in schools. The functions of various components in the model vehicle are described using appropriate schematics, and the impact of the device on classroom pedagogy was assessed over three years. The study found that the method can be used in schools to teach automotive technology and highlight the benefits of recycling waste materials. Therefore, we anticipate that our work will pique the curiosity of students and stimulate their imagination in preparation for the industry as it transitions toward e-mobility and eco-friendly manufacturing.

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Semiconductor Manufacturing Industry: Assessment, Challenges, and Future Trends 2

Semiconductor Manufacturing Industry: Assessment, Challenges...

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2nd international conference on Advanced Innovations in Smart Cities, ICAISC 2025

作者： Musa, Yasmin Tantawi, Khalid Mikhail, Maged Ma, Jeffrey Alharthi, Dalal Flatt, Larry Potter, Lyn Motlow State Community College Department of Career Readiness SmyrnaTN United States Department of Engineering Management and Technology University of Tennessee at Chattanooga TN United States Purdue University Northwest Hammond Department of Engineering Technology IN United States Saint Louis University Saint Louis Department of Mechanical Engineering MO United States College of Applied Science and Technology University of Arizona Tuscan AZ United States Robotics and Automation Center Motlow State Community College McMinnvilleTN United States Chattanooga State Community College Chattanooga State Community College Dept. of Engineering Systems Tech. ChattanoogaTN United States

ISBN: (纸本)9798331506995

In this work we evaluate the state of the semiconductor manufacturing industry and its challenges and trends. Future trends in the industry are analyzed from three perspectives: the evolution of Industry 4.0, the advances in semiconductor materials, and the impact of the Covid-19 Pandemic. The semiconductor manufacturing industry witnessed an acute decline in the United States and other regions in the two decades prior to the CoVid-19 pandemic. The decline was only uncovered after the chip shortage of 2021 that resulted from the severe supply chain disruption. Trends in the industry were analyzed from three perspectives: Industry 4.0, advances in materials, and the Post-pandemic era. As a result of the evolution of the fourth generation of industry (Industry 4.0), trends in semiconductor manufacturing include robotization, which caused the industry to become the largest market for industrial robotics since 2020, and an all-time peak globalization. The semiconductor industry is a very globalized industry with corporates from different parts of the world taking part in the production of the final product. Although some materials such as carbon and Gallium Nitride show promising trends to replace silicon as the material of choice. It will likely not be before two or three decades when a semiconductor material will be able to replace silicon. Challenges for the industry include the shortage of the trained-workforce, and the added inter-country restrictions that may hinder the globalization of the industry. © 2025 IEEE.

关键词： Semiconductor alloys

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