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2023 China automation Congress, CAC 2023

作者： Wang, Huai Cui, Bo Wen, Xingfen Jiang, Yang Gao, Chongjin Tian, Yibin Co. Ltd. Shenzhen China Guangdong Jaten Robot Automation Co. Ltd. Shenzhen China College of Mechatronics and Control Engineering Shenzhen University Shenzhen China

ISBN: (纸本)9798350303759

In modern industrial settings, pallets are necessary to logistics transportation. This often necessitates the use of forklifts for pallet handling. However, steer and controlling forklifts require a high level of skill. Traditional methods have struggled to adapt to the rapid pace of businesses development, severely impairing normal production and operational efficiency. We describe a method for automatic detection and positioning of pallets that can be used on Automatic Guided Vehicle (AGV) forklifts. The algorithm initially employs a deep neural network (DNN) approach to learning salient features of the pallets in RGB and depth images, thereby achieving localization. Subsequently, the point cloud of the target area is filtered and matched to obtain the orientation information of the pallets. The entire calculation process can run in real-time on low-scale edge computing devices, and both RGB and depth data come from low-cost TOF cameras. In the experimental section, we study the stability and accuracy of the algorithm in several typical and special scenarios. The results show that our method is robust in normal scenarios and outperforms other methods in special scenarios, with a running time of less than 1300 milliseconds. For the logistics industry, this is a promising solution. © 2023 IEEE.

关键词： Object detection

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Simulation And Real Time Of VR Controlled Robotic Manipulator Using ROS 4

Simulation And Real Time Of VR Controlled Robotic Manipulato...

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4th IEEE Bombay Section Signature Conference, IBSSC 2022

作者： Vairavasamy, Sasidharan Noel Innocent, J. Hamin, M.J. Ahmed, Syed Seenu, N. Mm Dean, Ramya Hindustan Institute of Technology and Science Department of Mechatronics Engineering Chennai India Centre for Automation and Robotics Department of Mechatronics Engineering Hindustan Institute of Technology and Science Chennai India Agurchand Manmull Jain College Chennai India

ISBN: (纸本)9781665492911

This paper focuses on developing a virtually controlled robot by integrating Virtual Reality (VR) and Robot Operating System (ROS). Robots can be used in certain environments where humans cannot be physically present to undertake a task. To increase the safety of humans, controlling a robot virtually is one of the best solutions. This paper shows how the VR-controlled manipulator will help in different fields like hazardous environments, underwater research, and the medical field for surgical operations. Unity 3D is used to develop the virtual environment, and ROS is used for communication with the physical robot. A Virtual environment would be developed where an exact robot (URDF) model can be designed. The interaction with the virtual environment is done with the help of VR headsets and controllers. ROS acts as the communication bridge between virtual and physical robots. A prototype has been developed to be controlled through virtual controllers that can interact through ROS. © 2022 IEEE.

关键词： Virtual reality

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High-performance triboelectric nanogenerator based on ZrB_(2)/polydimethylsiloxane for metal corrosion protection

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International Journal of Minerals,Metallurgy and Materials 2023年第10期30卷 1957-1964页

作者： Xiucai Wang Naijian Hu Jia Yang Jianwen Chen Xinmei Yu Wenbo Zhu Chaochao Zhao Ting Wang Min Chen School of Materials Science and Hydrogen Energy Guangdong Key Laboratory for Hydrogen Energy TechnologiesFoshan UniversityFoshan 528000China School of Electronic and Information Engineering Foshan UniversityFoshan 528000China Mechatronics Engineering and Automation College Foshan UniversityFoshan 528200China Department of Biomedical Engineering School of MedicineFoshan UniversityFoshan 528225China Guangdong Provincial Key Laboratory of Electronic Functional Materials and Devices Huizhou UniversityHuizhou 516001China

Metal corrosion causes billions of dollars of economic losses *** a smart and new energy-harvesting device,triboelectric nanogenerators(TENGs)can convert almost all mechanical energy into electricity,which leads to great prospects in metal corrosion prevention and cathodic *** this work,flexible TENGs were designed to use the energy harvested by flexible polydimethylsiloxane(PDMS)films with ZrB_(2)nanoparticles and effectively improve the dielectric constant by incorporating ZrB_(2).The open-circuit voltage and short-circuit current were 264 V and 22.9μA,respectively,and the power density of the TENGs reached 6 W·m^(-2).Furthermore,a selfpowered anti-corrosion system was designed by the rectifier circuit integrated with TENGs,and the open-circuit potential(OCP)and Tafel curves showed that the system had an excellent anti-corrosion effect on carbon ***,the system has broad application prospects in fields such as metal cultural relics,ocean engineering,and industry.

关键词： ZrB_(2) triboelectric nanogenerator self-powered corrosion protection

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Entropy-based Keyframe Established and Accelerated Fast LiDAR Odometry and Mapping 7

Entropy-based Keyframe Established and Accelerated Fast LiDA...

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7th IEEE Information Technology and mechatronics engineering Conference, ITOEC 2023

作者： Zeng, Qihua Liu, Dong Zhou, Yang Peng, Yaxin Shanghai University School of Mechatronics Engineering and Automation Shanghai200444 China Midea Group Ai Innovation Center Shanghai China Shanghai University Department of Mathemat College of Sciences Shanghai200444 China

ISBN: (纸本)9798350334197

With the advancement of computer computing power, most of the current SLAM (Simultaneous Localization and Mapping) algorithms use graph optimization to build graphs. The key to graph optimization is to establish nodes and edges, that is keyframes and pose constraints. However, most algorithms still use heuristic methods to determine whether to establish new keyframes. This method usually creates redundant keyframes, adding invalid nodes to the graph optimization process, which results in lower efficiency of back-end optimization. Moreover, the frequent creation of keyframes leads to the need for frequent updates to the local map in front-end point cloud matching, reducing its efficiency. In this paper, we introduce an information-theoretic method for deciding when to generate new keyframes and optimizing updates to the local map for better front-end point cloud matching. Specifically, we calculate the information entropy of each point cloud matching pose. Once it reaches the set threshold, it indicates that the previous local map does not provide sufficient information for point cloud matching, which necessitates the establishment of a new keyframe. The local map is also updated immediately. This proposed method can establish keyframes with sufficient information and improve the accuracy of point cloud matching in the public dataset evaluation. © 2023 IEEE.

关键词： Mapping

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Advances in 3D printing of magnetic materials:Fabrication,properties,and their applications

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Journal of Advanced Ceramics 2022年第5期11卷 665-701页

作者： Xiangxia WEI Ming-Liang JIN Haiqiang YANG Xiao-Xiong WANG Yun-Ze LONG Zhangwei CHEN Institute for Future School of AutomationShandong Key Laboratory of Industrial Control TechnologyQingdao UniversityQingdao 266071China Collaborative Innovation Center for Nanomaterials&Devices College of PhysicsQingdao UniversityQingdao 266071China Additive Manufacturing Institute College of Mechatronics and Control EngineeringShenzhen UniversityShenzhen 518060China

Magnetic materials are of increasing importance for many essential applications due to their unique magnetic ***,due to the limited fabrication ability,magnetic materials are restricted by simple geometric ***-dimensional(3D)printing is a highly versatile technique that can be utilized for constructing magnetic *** shape flexibility of magnets unleashes opportunities for magnetic composites with reducing post-manufacturing costs,motivating the review on 3D printing of magnetic *** paper focuses on recent achievements of magnetic materials using 3D printing technologies,followed by the characterization of their magnetic properties,which are further enhanced by ***,the corresponding properties depend on the intrinsic nature of starting materials,3D printing processing parameters,and the optimized structural *** emphasis is placed on the functional applications of 3D-printed magnetic materials in different ***,the current challenges and future opportunities are also addressed.

关键词： three-dimensional(3D)printing hard magnets soft magnets magnetic properties applications

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Tire Defect Detection Based on Improved DeepLabv3+

Tire Defect Detection Based on Improved DeepLabv3+

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Chinese Control Conference (CCC)

作者： Xiaoyu Lil Chen Peng Department of Automation College of Mechatronics Engineering and Automation Shanghai University Shanghai P. R. China

Tire defect detection is an essential step to control product quality, and accurate segmentation is the key to product grading. However, due to the fact that the internal defects of tires need to be judged manually through X-ray imaging, as well as the complex background and various types of defects, the grading of defects is marked differently, and the accuracy is affected by subjective factors. An improved algorithm based on DeepLabv3+ is proposed in this paper to solve the above problems. Firstly, the high-level semantic and low-level position features of image is integrate by encoder-decoder structure, which can face any input size. Secondly, atrous spatial pyramid pooling module and lightweight mobilnetv2 backbone can be used to accurately segment defects of different shapes and sizes, and reduce edge calculation pressure. The experimental results show that the improved deeplabv 3+ can detect different defects, while the accuracy performance of model is improved to 81.42% MIoU.

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Prediction of Environmental Parameters of Yungang Grottoes Based on BO-CNN-LSTM Artificial Neural Network 8th

Prediction of Environmental Parameters of Yungang Grottoes B...

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8th International Conference on Life System Modeling and Simulation, LSMS 2024 and 8th International Conference on Intelligent Computing for Sustainable Energy and Environment, ICSEE 2024

作者： Gao, Lunrui Yan, Hongbin Liu, Tingzhang Zhang, Shaoyou Xu, Xinrui Department of Automation College of Mechatronics Engineering and Automation Shanghai University Shanghai China Cultural Heritage Protection and Monitoring Center Yungang Research Institute Shanxi China

ISBN: (纸本)9789819602933

This paper introduces a method for predicting internal environmental parameters of the Yungang Grottoes using a hybrid approach that combines Long Short-Term Memory (LSTM) neural networks with Convolutional Neural Network (CNN) technology. To enhance the predictive accuracy, the Bayesian Optimization algorithm was employed to optimize the most relevant hyperparameters of the proposed model. The study utilized a database obtained from external weather stations and internal cave sensors as a sample set to train the model. Initially, a preprocessing algorithm was applied to improve data quality and prediction accuracy. Subsequently, the developed model was utilized to forecast the environmental parameters inside the cave under external conditions. The obtained results were compared with other model types: LSTM neural networks and CNN-LSTM hybrid neural networks. The findings indicate that the proposed model surpasses the comparative models in terms of prediction accuracy and quality across all analyzed parameters. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Prediction models

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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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Multi-objective Optimal Operation of Centralized Battery Swap Charging System with Photovoltaic

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Journal of Modern Power Systems and Clean Energy 2022年第1期10卷 149-162页

作者： Yuanzheng Li Yihan Cai Tianyang Zhao Yun Liu Jian Wang Lei Wu Yong Zhao School of Artificial Intelligence and Automation Ministry of Education Key Laboratory of Image Processing and Intelligence ControlHuazhong University of Science and TechnologyWuhanChina School of Electrical and Electronic Engineering Nanyang Technological UniversitySingaporeSingapore College of Mechatronics and Control Engineering Shenzhen UniversityShenzhenChina Department of Electrical&Computer Engineering Stevens Institute of TechnologyHobokenUSA

Electric vehicles(EVs)are widely deployed throughout the world,and photovoltaic(PV)charging stations have emerged for satisfying the charging demands of EV *** paper proposes a multi-objective optimal operation method for the centralized battery swap charging system(CBSCS),in order to enhance the economic efficiency while reducing its adverse effects on power *** proposed method involves a multi-objective optimization scheduling model,which minimizes the total operation cost and smoothes load fluctuations,***,we modify a recently proposed multi-objective optimization algorithm of non-sorting genetic algorithm III(NSGA-III)for solving this scheduling ***,simulation studies verify the effectiveness of the proposed multi-objective operation method.

关键词： Multi-objective optimization electric vehicle battery swap charging system scheduling photovoltaic

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Analysis of Connection Optimization in Planar Transformer Winding Loss 2

Analysis of Connection Optimization in Planar Transformer Wi...

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2nd IEEE International Power Electronics and Application Symposium, PEAS 2023

作者： He, Mou Xie, JingYi Yang, Lei Chen, Wei Lin, SuBin Chen, QingBin Huang, Yuping College of Electrical Engineering and Automation FuZhou University Fuzhou China School of Electronic Electrical Engineering and Physics Fujian University of Technology Fuzhou China Beijing Institute of Precision Mechatronics and Controls Laboratory of Aerospace Servo Actuation and Transmission Beijing China

ISBN: (纸本)9798350313765

Plane transformers are vital components of high-frequency power electronic converters, and the calculation and optimal design of their parallel winding losses pose significant challenges in the design process. This article proposes a theoretical calculation method for winding losses based on impedance matrix and circuit equations, and it derives the significance and acquisition methods of impedance matrix parameters under high-frequency conditions. Building upon the proposed theoretical calculation method for winding losses, the article performs classification analysis of circuit equations to determine the constraints of the optimization problem. It establishes a mathematical model for optimizing winding losses in a single topology and provides a general solution method for designing the optimal structure of winding losses. Finally, experimental measurements are conducted to validate the effectiveness of the optimization method presented in this article. © 2023 IEEE.

关键词： multi-layer connection optimal parallel winding planar transformer winding loss

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