检索结果-内蒙古大学图书馆

20th IEEE International Conference on Mechatronics and Automation, ICMA 2023

作者： Yang, Fanhang Dong, Enzeng Tong, Jigang Yang, Sen Du, Shengzhi Tianjin University of Technology Tianjin Key Laboratory for Control Theory & Applications in Complicated Systems Intelligent Robot Laboratory 391 Binshui West Road Xiqing District Tianjin China Tshwane University of Technology Department of Electrical Engineering Pretoria0001 South Africa

ISBN: (纸本)9798350320831

We present a two-stage 3D object detection framework from point clouds, named Point Density-aware Channel-wise Transformer (PD-CT3D), which investigate the property of point density. This architecture uses 3D sparse CNN to effectively generate high-quality proposals at the first stage, then integrates the inherent property of point density and 3D CNN-based voxel features by density-aware proposal grid pooling. Specifically, each generated proposal from the first stage is divided into grids to aggregate corresponding voxel-wise features and raw point-based features for encoding the representative features from the whole scene. Subsequently, a channel-wise encoder-decoder transformer is adopted to extract the encoded density-aware features and decode them into a global representation for final refinement. Experiments on the widely used KITTI dataset show that the PD-CT3D achieves competitive performance among state-of-the-art methods. © 2023 IEEE.

关键词： Object detection

来源：评论

学校读者我要写书评

暂无评论

Nondestructive evaluation of austenitic stainless steel using CIC-MFL and LIHaS

Nondestructive evaluation of austenitic stainless steel usin...

引用

作者： Jun, Jongwoo Choi, Myungki Lee, Jinyi Research Center for Real Time NDT Chosun University Gwangju 501-759 Korea Republic of Department of Information and Communication Engineering Graduate School of Chosun University Gwangju 501-759 Korea Republic of Department of Control Instrumentation and Robot Engineering Chosun University Gwangju 501-759 Korea Republic of

Austenitic stainless steels (A-SS) are extensively used in widespread industrial and technological applications due to their good corrosion resistance combined with their relatively high strength, toughness, and stiffness. However, sometimes a small amount of partial magnetization is generated in A-SS due to imperfect final heat treatments and mechanical processing, such as rolling and welding. These partially magnetized regions may be misidentified as a crack when tested using conventional nondestructive methods. This paper presents a nondestructive evaluation approach using a linearly integrated Hall sensor array (LIHaS) and a combined induced current and magnetic flux leakage (CIC-MFL) method in order to ensure reliable crack inspections for A-SS. © 2011 IEEE.

关键词： Austenitic stainless steel

来源：评论

学校读者我要写书评

暂无评论

Volume measurement method for 2D connector inspection machine

引用

Journal of Institute of control, robotics and Systems 2017年第9期23卷 780-785页

作者： Kwon, Soon-Sub Park, Tae-Hyoung Department of Control and Robot Engineering Chungbuk National University Korea Republic of School of Electronics Engineering and Research Institute for Computer and Information Communication Chungbuk National University Korea Republic of

The connector inspection machine is the AOI equipment used to detect defective connectors. We developed the 4-side connector inspection machine that can acquire images from four sides simultaneously using a single camera and four mirrors. The volume size should be measured to detect the abnormal molding defect. However, the inspection machine can acquire only a 2D image of each side of the connector. To measure the volume, we reconstructed 3D images from 2D images of four sides. The epipolar geometry and homography were used to improve the accuracy of the matching between other side images. The experimental results are presented that verify the usefulness of the method. © ICROS 2017.

关键词： Volume measurement

来源：评论

学校读者我要写书评

暂无评论

Grain-level visualization of stress-strain distribution on fatigue crack via self-magnetic flux density: a brief experimental investigation

Grain-level visualization of stress-strain distribution on f...

引用

IEEE Instrumentation and Measurement Technology Conference

作者： I Dewa Made Oka Dharmawan Jinvi Lee Deparment of Control Intrumentation and Robot Engineering Chosun University Gwangju Republic of Korea Department of Electronic Engineering Chosun University Gwangju Republic of Korea

ISBN: (数字)9798350380903

ISBN: (纸本)9798350380910

Fatigue cracks exhibit unpredictable and rapid propagation, presenting challenges in comprehending their initiation, influenced by various physical and chemical parameters. To gain deeper insights into the nucleation and growth, understanding the convergence phenomenon in ferromagnetic materials requires visualization of the local stresses and phase changes around the defect. This necessitates a measurement system capable of not only imaging the defect but also stress mapping at high spatial resolution, ideally at grain-level. In this study, we explore how this can be achieved by integrating three-axis tunnel magnetoresistive (TMR) sensor with optical microscopy images. This integration was expected to facilitate the visualization of self-magnetic flux density and enable microstructure analysis on the material's surface. Employing this mapping technique, we observe and discuss the stress distribution around the crack at the grain level with three variation of defect depths direction: 0, 30, and 60 degrees.

关键词： Microscopy Data visualization Fatigue Tunneling magnetoresistance Spatial resolution Surface cracks Stress

来源：评论

学校读者我要写书评

暂无评论

Localization system for AGVs using laser scanner and marker sensor

引用

Journal of Institute of control, robotics and Systems 2017年第10期23卷 866-872页

作者： Heo, Sung-Woo Park, Tae Hyoung Department of Control and Robot Engineering Chungbuk National University Korea Republic of Department of Electronics Engineering Chungbuk National University Research Institute for Computer and Information Communication Chungbuk National University Korea Republic of

This study develops a localization system using marker sensors and a laser scanner for autonomous guided vehicles (AGVs). To calibrate the relative position data of robots, which are obtained from encoders and gyros, the system uses a laser scanner and magnetic markers. The existing position-tracking method distinguish between rail and non-rail. This study proposes a method that enhances the position accuracy of robots using marker sensors and a laser scanner without distinguishing between rail and non-rail. First, using a laser scanner, the robot positions are obtained by measuring the distance between the reflector and the robot. The magnetic marker sensors provide the absolute position by detecting magnetic landmarks. Using a Kalman filter to combine the position data retrieved from the two sensors with the position data from the encoders and gyro sensors, we propose an effective localization system that integrates rails and non-rails. The experiment was repeated at three places using an actual AGV that was developed for this study. The experimental results demonstrate that the proposed system can effectively track the positions of AGVs. © ICROS 2017.

关键词： robots

来源：评论

学校读者我要写书评

暂无评论

Accurate RGB-D SLAM in dynamic environments based on dynamic visual feature removal

引用

Science China(Information Sciences) 2022年第10期65卷 256-269页

作者： Chenxin LIU Jiahu QIN Shuai WANG Lei YU Yaonan WANG Department of Automation University of Science and Technology of China Institute of Artificial Intelligence Hefei Comprehensive National Science Center College of Electrical and Information Engineering Hunan University National Engineering Research Center of Robot Visual Perception and Control Technology Hunan University

Visual localization is considered an essential capability in robotics and has attracted increasing interest for the past few years. However, most proposed visual localization systems assume that the surrounding environment is static, which is difficult to maintain in real-world scenarios due to the presence of moving objects. In this paper, we present DFR-SLAM, a real-time and accurate RGB-D SLAM based on ORB-SLAM2 that achieves satisfactory performance in a variety of challenging dynamic scenarios. At the core of our system lies a motion consensus filtering algorithm estimating the initial camera pose and a graph-cut optimization framework combining long-term observations, prior information, and spatial coherence to jointly distinguish dynamic and static visual features. Other systems for dynamic environments detect dynamic components by using the information from short time-span frames, whereas our system uses observations from a long period of keyframes. We evaluate our system using dynamic sequences from the public TUM dataset, and the evaluation demonstrates that the proposed system outperforms the original ORB-SLAM2 system significantly. In addition, our system provides competitive localization accuracy with satisfactory real-time performance compared to closely related SLAM systems designed to adapt to dynamic environments.

关键词： SLAM dynamic environments indoor localization graph-cut robot navigation

来源：评论

学校读者我要写书评

暂无评论

Task-oriented synchronous error monitoring framework in robotic manufacturing process

Task-oriented synchronous error monitoring framework in robo...

引用

IEEE International Conference on Automation Science and engineering (CASE)

作者： Hyungsik Kim Joono Cheong Seungik Lee Joongbae Kim Department of Control and Instrumentation Engineering Korea University South Korea Intelligent Robot Control Research Team Electronics and Telecommunications Research Institute Daejeon South Korea

As manufacturing systems become increasingly more automated and complicated, there is a need for supervision systems to operate and control production. In complex manufacturing environments, robots can make errors that can cause serious product damages. This paper focuses on the efficient supervision systems, called the sequential task-oriented supervision, using multiple sensors for achieving task status monitoring, automated error analysis in robotic manufacturing process. As with the designed task sequence, a status monitoring system runs synchronously to detect errors in the current robot task. In order to continue performing tasks without human intervention, task status monitoring systems use multiple sensors including a vision sensor, a force-torque(F/T) sensor and a tactile sensor is developed. Detailed structure and working principle of the monitoring system are addressed in this paper.

关键词： Monitoring Sensor fusion robot sensing systems Sensor systems Manufacturing processes

来源：评论

学校读者我要写书评

暂无评论

The data mining of time-series of flow supply chain based on time-delayed NNET

The data mining of time-series of flow supply chain based on...

引用

International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Chen Peng Dong Yue Shi-Fan Xu The Department of control theory and Engineering Nanjing Normal University China The center of Cims and Robot Chinese University of Mine and Technology China

ISBN: (纸本)0780375084

In the paper, aiming at the question of knowledge discovery of the large quantities of time-series data in continuous flow supply chains, the project of KDD based on integrated information is presented and a time-delayed NN is applied. Under the premise of integration of the network data, a Visual Basic program is used to distill data and a VB engine is cited, NNET tools of MATLAB are utilized to find the pattern of time-series, forecasting the rules of data, and supervising the optimal operation of a supply chain.

关键词： Data mining Supply chains Neural networks Production Marketing and sales Pattern analysis control theory Data engineering Knowledge engineering Computer integrated manufacturing

来源：评论

学校读者我要写书评

暂无评论

Magnetic images of surface crack on heated specimen using an area-type magnetic camera with high spatial resolution

Magnetic images of surface crack on heated specimen using an...

引用

IEEE Instrumentation and Measurement Technology Conference

作者： Jiseong Hwang Jungmin Kim Jinyi Lee Department of Information and Communication Engineering Graduate School Chosun University Gwangju South Korea Department of Control and Instrumentation Robot Engineering Chosun University Gwangju South Korea

A micro-array method using Hall sensors was proposed in previous research by the authors. That array method allowed a two-dimensional magnetic field measurement with high spatial resolution using simplified connections. A wide range of magnetic fields could be measured quantitatively with high spatial resolution. This paper proposes a nondestructive testing (NDT) method using a magnetic camera with the previous micro-array method to detect cracks in a specimen at high temperatures. Distilled water has a boiling point of 373.15 K at atmospheric pressure. Therefore, the Hall sensor array, which is submerged in the distilled water, can be protected from an external high temperature of several hundred degrees Kelvin until the container is broken. If the Hall voltage of each Hall sensor changes according to the external magnetic field at the boiling point of the liquid, we propose that the crack can be detected in a high temperature environment using a magnetic camera submerged in the liquid. Plate specimens made of SS41 stainless steel, with slits in the each specimen, were used to verify the proposed NDT method using a high spatial magnetic camera in a high temperature environment.

关键词： Surface cracks Cameras Spatial resolution Temperature sensors Magnetic sensors Magnetic field measurement Sensor arrays Magnetic liquids Atmospheric measurements Nondestructive testing

来源：评论

学校读者我要写书评

暂无评论

LimeSoDa: A Dataset Collection for Benchmarking of Machine Learning Regressors in Digital Soil Mapping

arXiv

引用

arXiv 2025年

作者： Schmidinger, Jonas Vogel, Sebastian Barkov, Viacheslav Pham, Anh-Duy Gebbers, Robin Tavakoli, Hamed Correa, Jose Tavares, Tiago R. Filippi, Patrick Jones, Edward J. Lukas, Vojtech Boenecke, Eric Ruehlmann, Joerg Schroeter, Ingmar Kramer, Eckart Paetzold, Stefan Kodaira, Masakazu Wadoux, Alexandre M.J.-C. Bragazza, Luca Metzger, Konrad Huang, Jingyi Valente, Domingos S.M. Safanelli, Jose L. Bottega, Eduardo L. Dalmolin, Ricardo S.D. Farkas, Csilla Steiger, Alexander Horst, Taciara Z. Ramirez-Lopez, Leonardo Scholten, Thomas Stumpf, Felix Rosso, Pablo Costa, Marcelo M. Zandonadi, Rodrigo S. Wetterlind, Johanna Atzmueller, Martin Osnabrück University Joint Lab Artificial Intelligence and Data Science Osnabrück Germany Department of Agromechatronics Potsdam Germany Piracicaba Brazil The University of Sydney Sydney Institute of Agriculture Sydney Australia Mendel University in Brno Department of Agrosystems and Bioclimatology Brno Czech Republic Leibniz Institute of Vegetable and Ornamental Crops Next Generation Horticultural Systems Grossbeeren Germany Eberswalde University for Sustainable Development Landscape Management and Nature Conservation Eberswalde Germany Soil Science and Soil Ecology Bonn Germany Tokyo University of Agriculture and Technology Institute of Agriculture Tokyo Japan LISAH Univ. Montpellier AgroParisTech INRAE IRD L'Institut Agro Montpellier France Agroscope Field-Crop Systems and Plant Nutrition Nyon Switzerland University of Wisconsin-Madison Department of Soil Science Madison United States Federal University of Viçosa Department of Agricultural Engineering Viçosa Brazil Woodwell Climate Research Center Falmouth United States Academic Coordination Santa Maria Brazil Soil Department Santa Maria Brazil Division of Environment and Natural Resources Aas Norway University of Rostock Chair of Geodesy and Geoinformatics Rostock Germany Federal Technological University of Paraná Dois Vizinhos Brazil BÜCHI Labortechnik AG Data Science Department Flawil Switzerland Imperial College London Imperial College Business School London United Kingdom University of Tübingen Department of Geosciences Tübingen Germany University of Tübingen DFG Cluster of Excellence Machine Learning for Science’ Germany Bern University of Applied Sciences Competence Center for Soils Zollikofen Switzerland Simulation and Data Science Müncheberg Germany Federal University of Jataí Institute of Agricultural Sciences Jatai Brazil Federal University of Mato Grosso Instute of Agricultural and Environmental Scinces Sinop Brazil Department of Soil and Environment Skara

Digital soil mapping (DSM) relies on a broad pool of statistical methods, yet determining the optimal method for a given context remains challenging and contentious. Benchmarking studies on multiple datasets are needed to reveal strengths and limitations of commonly used methods. Existing DSM studies usually rely on a single dataset with restricted access, leading to incomplete and potentially misleading conclusions. To address these issues, we introduce an open-access dataset collection called Precision Liming Soil Datasets (LimeSoDa). LimeSoDa consists of 31 field- and farm-scale datasets from various countries. Each dataset has three target soil properties: (1) soil organic matter or soil organic carbon, (2) clay content and (3) pH, alongside a set of features. Features are dataset-specific and were obtained by optical spectroscopy, proximal- and remote soil sensing. All datasets were aligned to a tabular format and are ready-to-use for modeling. We demonstrated the use of LimeSoDa for benchmarking by comparing the predictive performance of four learning algorithms across all datasets. This comparison included multiple linear regression (MLR), support vector regression (SVR), categorical boosting (CatBoost) and random forest (RF). The results showed that although no single algorithm was universally superior, certain algorithms performed better in specific contexts. MLR and SVR performed better on high-dimensional spectral datasets, likely due to better compatibility with principal components. In contrast, CatBoost and RF exhibited considerably better performances when applied to datasets with a moderate number ( © 2025, CC BY-SA.

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：