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检索条件"任意字段=2nd International Conference on Robotics Systems and Vehicle Technology, RSVT 2020"

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rsvt 2020 - Proceedings of 2020 2nd international conference on robotics systems and vehicle technology

RSVT 2020 - Proceedings of 2020 2nd International Conference...

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2nd international conference on robotics systems and vehicle technology, rsvt 2020

ISBN: (纸本)9781450389068

The proceedings contain 21 papers. The topics discussed include: fuzzy comprehensive evaluation of customer satisfaction of high speed rail express based on AHP;evolutionary analysis of Chinese high-speed railways network;subway network critical nodes detection based on improved PageRank algorithm;detection method for polygonalization of wheel treads based on dynamic response;a test cases generation method for ATP;the impact of China railway express on urban economic development;study on the construction and application of the water emergency rescue equipment system;research on the application of WLSM in ship traffic fundamental diagram model;analysis of vessel abnormal behavior detection;and research on optimization of the container exchange mode of cross-border highway transportation between china and Vietnam

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Purely Visual Loading: Pose-Classification Network for Loading Service Robot onto Ego-vehicle 2nd

Purely Visual Loading: Pose-Classification Network for Load...

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2nd international conference on the Frontiers of robotics and Software Engineering, FRSE 2024

作者： Nie, Yixiao Jin, Yingjie Wang, Zhepeng Li, Xiu Li, Xiang Shenzhen Tsinghua International Graduate School Tsinghua University Beijing China Lenovo Research Beijing China Department of Automation Tsinghua University Beijing China

ISBN: (纸本)9789819630127

This paper develops a new vehicle-robot system, where an autonomous ego-vehicle carries service robots and sends them out to the desired location to perform a specific task (e.g., inspection, cleaning, transportation), and it retrieves them after the task. Specifically, this paper proposes a new pose classification network at the retrieval stage. With such a network, the robot can be navigated to approach the ego-vehicle. When it is close enough, the robot can identify the structured features (e.g., AR codes) and board the vehicle. The constructed network has the advantage of being small-scale and is suitable for the implementation of the mobile robot without sacrificing the positioning accuracy. It allows the robot to use purely visual information to board the vehicle without any additional communication or sensory measures. Hence, it can be applicable to scenarios where the structured features are far away or the lidar is not within the sensory zone. Experimental results are presented to validate the performance of the proposed method. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Mobile robots

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Conceptual Design of a Low Cost Underwater Glider for Educational Purpose 2nd

Conceptual Design of a Low Cost Underwater Glider for Educat...

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2nd international conference on Mechanical Engineering, INCOM 2024

作者： Dhulekar, A.M. Sharma, F. Dixit, U.S. Indian Institute of Technology Guwahati Technology Innovation and Development Foundation Guwahati India Centre for Indian Knowledge Systems Indian Institute of Technology Guwahati Guwahati India Department of Mechanical Engineering Indian Institute of Technology Guwahati Guwahati India

ISBN: (纸本)9789819772957

An underwater glider is a special type of remotely operated underwater vehicle employed for research and monitoring the underwater environment. This article presents the design and fabrication of an underwater glider specifically for educational purposes. The three-dimensional model of the glider is developed using Computer Aided Design (CAD) software. Important parameters, viz., buoyancy control system, rolling mechanism, electronics and control system and wing design are described. The buoyancy mechanism used for the propulsion differentiates a glider from other underwater vehicles. The design parameters, specifications and dimensions of the fabricated glider are highlighted. The design incorporates a unique feature, viz., a movable ballast tank for adjusting both buoyancy and altitude. To achieve a lightweight structure, 3D printing technology employing plastic raw material was utilized. Computational analysis of the CAD model of the glider was carried out to investigate the variation of hydrodynamic parameters. The educational significance of this work lies in its potential to enhance the educators’ and students’ understanding of remotely operated underwater vehicles as well as nurturing hands-on learning experiences. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Buoyancy

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Electric vehicle Charging Navigation Using Waterwheel Plant Algorithm for Coordinating Smart Grids and Intelligent Transportation systems 2

Electric Vehicle Charging Navigation Using Waterwheel Plant ...

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2nd international conference on Machine Learning and Autonomous systems, ICMLAS 2025

作者： Siva Ramkumar, M. Sivaramkrishnan, M. Uday, Kaparthi Kanan, Mohammad Mohan Raj, C. Giri, Jayant SNS College of Technology Dept of ECE India Karpagam College of Engnieering Dept of EEE India CVR College of Engineering EIE Department Hyderabad India College of Engineering University of Business and Technology Department of Industrial Engineering Jeddah21448 Saudi Arabia College of Engineering Zarqa University Department of Mechanical Engineering Zarqa Jordan Centre for Robotics and Industrial Automation Sri Eshwar College of Engineering Department or EEE Coimbatore641202 India Yeshwantrao Chavan College of Engineering Department of Mechanical Engineering Nagpur India Lovely Professional University Division of Research and Development Phagwara India

ISBN: (纸本)9798331505745

The efficient charging of electric vehicles (EVs) remains essential to create sustainable mobility while EVs transform into crucial elements of upcoming transportation systems. The present EV charging navigation systems deal with three main issues including grid congestion and inadequate charging station (CS) selection and delays from traffic *** paper proposes a novel Waterwheel Plant Algorithm (WWPA) for optimizing EV charging navigation within the Smart Grid (SG) and Intelligent Transportation systems (ITS). The suggested method strives to enhance SG-EV coordination through demand balancing in addition to charge price reduction and decreased grid congestion levels. WWPA algorithm serves as the proposed method to optimize EV charging schedules. The MATLAB platform serves as the implementation environment for the proposed method which demonstrates superior performance than Multi-agent Reinforcement Learning (MARL), Deep Reinforcement Learning (DRL), Coati-Northern Goshawk Optimization (Coati-NGO) and Grey Sail Fish Optimization (GSFO). Results demonstrate that the WWPA algorithm reduces average charging expenses by 18.14% throughout diverse charging operations as it produces superior performance than existing algorithms operating in the SG ITS. © 2025 IEEE.

关键词： Reinforcement learning

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Reconfigurable Smart Grid Management for Electric vehicle Charging and the Integration of Renewable Energy Sources using Pied Kingfisher Optimizer 2

Reconfigurable Smart Grid Management for Electric Vehicle Ch...

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2nd international conference on Machine Learning and Autonomous systems, ICMLAS 2025

作者： Sivaramkrishnan, M. Ramkumar, M. Siva Uday, Kaparthi Kanan, Mohammad Raj, C. Mohan Giri, Jayant Karpagam College of Engnieering Dept of EEE India SNS College of Technology Dept of ECE India CVR College of Engineering Ibrahimpatanam EIE Department Hyderabad India College of Engineering University of Business and Technology Department of Industrial Engineering Jeddah21448 Saudi Arabia College of Engineering Zarqa University Department of Mechanical Engineering Zarqa Jordan Centre for Robotics and Industrial Automation Sri Eshwar College of Engineering Department or EEE Coimbatore641202 India Yeshwantrao Chavan College of Engineering Department of Mechanical Engineering Nagpur India Lovely Professional University Division of Research and Development Phagwara India

ISBN: (纸本)9798331505745

Electric vehicle (EV) charging management under the Smart Grid (SG) framework with incorporated Renewable Energy Sources (RESs) functions to advance Energy Management (EM). The operational cost of EV charging varies because renewable energy availability can change so this affects the financial performance of charging operations. Integration of RESs with the SG becomes challenging for operational system efficiency particularly when renewable energy generation levels are low. To overcome these drawbacks, this manuscript proposes an efficient approach for SG management for EV charging with the integration of RESs. The suggested method is Pied Kingfisher Optimizer (PKO). The main aim of the suggested technique is to minimize the operational expenses of EV charging as well as maximize the efficiency of the SG system. The PKO is used to optimize the scheduling and allocation of energy resources within the SG system. By then, the suggested approach is implemented in MATLAB and contrasted with several other methods that are currently in use. The suggested technique outperforms all existing approaches such as Bald Eagle Search (BES), Red Kite Optimization (RKO), Artificial Neural Network-Particle Swarm Optimization (ANN-PSO), and Coati Optimization Algorithm-Constitutive Artificial Neural Network (COA-CANN). The suggested approach delivers superior performance than conventional methods by reducing operational costs to 638,322$ under coordinated charging and 629,745$ under smart charging without impacting system performance metrics. © 2025 IEEE.

关键词： Particle swarm optimization (PSO)

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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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Semiconductor Manufacturing Industry: Assessment, Challenges, and Future Trends

Semiconductor Manufacturing Industry: Assessment, Challenges...

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Advanced Innovations in Smart Cities (ICAISC), international conference on

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

ISBN: (数字)9798331506995

ISBN: (纸本)9798331507008

关键词： Industries COVID-19 Pandemics Service robots Supply chains Globalization Semiconductor device manufacture Market research Silicon Fourth Industrial Revolution

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Deep Learning and IoT Based robotics to Monitor the Traffic 2nd

Deep Learning and IoT Based Robotics to Monitor the Traffic

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2nd international conference on Cyber Warfare, Security and Space Computing, SpacSec 2024

作者： Priya, V. Vishwa Pande, Soumitra S. Ilyas, Md Jayasudha, R. Ramesh, Janjhyam Venkata Naga Suganthi, D. Department of Computer Science Vels Institute of Science Technology and Advanced Studies Chennai India Ericsson Global India Private Limited Bangalore India Prestige Institute of Engineering Management and Research Indore India Dr. N. G. P. Institute of Technology Coimbatore India Koneru Lakshmaiah Education Foundation Andhra Pradesh Guntur Vaddeswaram India Saveetha College of Liberal Arts and Sciences SIMATS Thandalam Chennai India

ISBN: (纸本)9783031734939

In densely populated areas, managing traffic laws has become more difficult due to the rising number of cars on the road. One of the most critical components of effective traffic management and improved mobility is real-time traffic monitoring systems. Consequently, precise and dependable real-time traffic information has always been essential for cars and drivers. Many other approaches have been suggested as potential answers to the issues plaguing traffic conditions recently. A different approach is VCC or vehicle cloud computing. In addition, an advanced model called an Iot-aided robotic (IoRT), which uses cameras and Internet of Things (IoT) detector nodes to gather actual traffic information, has been created. Two deep learning methods, one based on improved LeNet-5 for real-time signs for traffic identification and the other on the Inception-V3 model for detecting and identifying traffic lights, are the critical contributions provided by this research effort. Additionally, to decrease road accidents, the ideal distance between barriers and ultrasonic sensors was determined by analyzing the timing and speed of ultrasonic waves. Data acquired by cameras and sensors is analyzed using a variety of image processing algorithms before being uploaded to the cloud and made accessible to commuters and drivers via a mobile app. According to the test findings, the suggested models are far more accurate. The expanded GTSRB (EGTSRB) dataset achieved 98.89% accuracy while the German Traffic Sign Recognition Benchmark (GTSRB) dataset achieved 98.23% accuracy using the modified LeNet-5. The second model achieved a precision of 99.7 percent using data from the Laboratory for the Intelligent and Safe Automobiles (LISA). The results of this study beat previous research on comparable traffic monitoring systems by 2.13% for traffic light recognition and detection and by 4.89% for traffic sign identification. © The Author(s), under exclusive license to Springer Nature Switzerland AG

关键词： Traffic signs

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Empirical evidence from China: What contributes to airline customers' positive behavioral intentions? 2

Empirical evidence from China: What contributes to airline c...

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2nd international conference on robotics systems and vehicle technology, rsvt 2020

作者： Wu, Ting Xu, Min Ouyang, Xu Yuen, Yu Po Department of Industrial and Systems Engineering The Hong Kong Polytechnic University 999077 Hong Kong

ISBN: (纸本)9781450389068

This study aims to advance our understanding of airline customers' decision-making processes by investigating the relationships between service quality, perceived value, customer satisfaction, and behavioral intention in the context of China. A conceptual model involving the constructs mentioned above and hypotheses to be examined is first developed, with the service quality measured by the improved AIRQUAL, a multiple-item scale including the dimensions of tangibles, reliability, responsiveness, assurance, and empathy. A quantitative research approach based on the development of a structured self-administered questionnaire is applied. Reliability and correlation analyses are conducted to examine the internal consistency of multiple-item scales and the validity of the conceptual model, respectively. Multiple linear regression analysis is employed to test the proposed hypotheses. Regression results reveal that assurance has a positive effect on both behavioral intention and perceived value. Responsiveness and empathy influence behavioral intention and customer satisfaction in a positive manner, respectively. In addition, both perceived value and customer satisfaction exert positive impacts on behavioral intention. Finally, the implications of these results as well as the recommendations for the management policy and practice of airlines are discussed. This study may serve as a useful guide for airlines to retain customers and maintain their profitability. © 2020 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Customer satisfaction

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A Wireless Inductive Sensing technology for Soft Pneumatic Actuators Using Magnetorheological Elastomers

A Wireless Inductive Sensing Technology for Soft Pneumatic A...

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2nd IEEE international conference on Soft robotics (RoboSoft)

作者： Wang, Hongbo Totaro, Massimo Blandin, Afroditi Astreinidi Beccai, Lucia IIT Ctr MicrobioRobot Genoa Italy SSSA BioRobot Inst Pisa Italy

ISBN: (纸本)9781538692608

This paper presents a novel wireless inductive sensing technology to measure body deformation of soft pneumatic actuators (SPAs). The proposed technology exploits a magnetorheological elastomer (MRE) both as actuator's highly deformable skin and as target of the inductive sensor. When the MRE skin is deformed by internal driving and/or external load, the distance between the MRE and sensing coil changes, thereby the inductance. A flat SPA with an MRE skin is developed as a case study to validate and evaluate the proposed technology. A multiphysics finite element model is built to simulate the characteristics of the soft actuator and sensor as a single system. Experimental results highlight that this inductive sensing technology can measure the skin deformation with an effective resolution as high as 3 mu m (RMS) at null deformation (50 mu m at maximum deformation), without any hysteresis. Moreover, with pressure information, it is possible to retrieve both the deformation caused by internal driving and external load. A typical pneumatic bending actuator was developed to demonstrate its easy implementation in soft actuators. The presented technology does not require wires or mechanical connections between electronics and the deformable body, providing a promising sensing solution for SPAs and other soft systems.

关键词： Robot sensing systems Skin Strain Actuators Inductance Soft robotics

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