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IEEE International Conference on Automation Science and engineering (CASE)

作者： J. S. Lee T. H. Park Department of Control and Robot Engineering Chungbuk National University Cheong1u-si Republic of Korea School of Electronics Engineering Chungbuk National University Cheong1u-si Republic of Korea

ISBN: (数字)9781728169040

ISBN: (纸本)9781728169057

This paper proposes a direction convolution (DC) with direction information added to solve the semantic segmentation problem. In the existing semantic segmentation, the edge of the detected object is not clear. To solve this problem, the model was trained by adding edge information. Also, coord convolution is used to add pixel location information, and DC is proposed to detect the edge accurately. DC is a method to add information about eight directions around a pixel for the model to train affinity for neighboring pixels. Using the cityscape dataset, this paper's experimental results show the usefulness of the proposed method.

关键词： Convolution Image edge detection Feature extraction Semantics Image segmentation Training Bicycles

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Polar-view based object detection algorithm using 3D low-channel lidar

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Journal of Institute of control, robotics and Systems 2019年第1期25卷 56-62页

作者： Kwon, Soon-Sub Park, Tae-Hyoung Department of Control and Robot Engineering Chungbuk National University Korea Republic of Department of Electronics Engineering Chungbuk National University Korea Republic of

In order for an autonomous vehicle to move, object detection is required to recognize the surrounding environment. The sensors used for object detection mainly use a camera and lidar. However, it is difficult to detect the camera because of its influence on the surrounding environment. Therefore, object detection using lidar is required. For lidar-based object detection, we mainly use a high-channel lidar with a high resolution. However, high-channel lidar is expensive and is difficult to commercialize. To solve this problem, object detection studies using low-channel lidar are underway. In this paper, we present an algorithm to find an object (vehicle or pedestrian) using three 3D low-channel lidar systems. First, we converted the data from the lidar to the polar view. Then, we input the converted polar view into YOLO v3 to predict the class and the region of interest (ROI) of the object. We used K-means to separate the background and the object from the image in the predicted ROI to find the object except for the background. Only the object area found last was converted back into 3D space to find the location of the object. © ICROS 2019.

关键词： Object detection

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P-WAE: Generalized patch-wasserstein autoencoder for anomaly screening

arXiv

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arXiv 2021年

作者： Zhang, Hui Chen, Yurong Wang, Yaonan Cao, Yihong Wu, Q.M. Jonathan Yang, Yimin National Engineering Laboratory of Robot Visual Perception and Control Technology School of Robotics Hunan University Changsha Hunan410082 China Department of Electrical and Computer Engineering University of Windsor WindsorONN9B3P4 Canada Department of Computer Science Lakehead University OntarioP7B 5E1 Canada Vector Institute TorontoM5G 1M1 Canada

To mitigate the inspector’s workload and improve the quality of the product, computer vision-based anomaly detection (AD) techniques are gradually deployed in real-world industrial scenarios. Recent anomaly analysis benchmarks progress to generative models. The aim is to model the defect-free distribution so that anomalies can be classified as out-of-distribution samples. Nevertheless, there are two disturbing factors that need researchers and deployers to prioritize: (i) the simplistic prior latent distribution inducing limited expressive capability;(ii) the collapsed mutual-dependent features resulting in poor generalization. In this paper, we propose a novel Patch-wise Wasserstein AutoEncoder (P-WAE) architecture to alleviate those challenges. In particular, a patch-wise variational inference model coupled with solving the jigsaw puzzle is designed, which is a simple yet effective way to increase the expressiveness and complexity of the latent manifold. This alleviates the blurry reconstruction problem. In addition, the Hilbert-Schmidt Independence Criterion (HSIC) bottleneck is introduced to constrain the over-regularization representation. Comprehensive experiments, conducted on the MVTec AD dataset, demonstrate the superior performance of our proposed method. © 2021, CC BY.

关键词： Anomaly detection

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Projected Sliced Wasserstein Autoencoder-based Hyperspectral Images Anomaly Detection

arXiv

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arXiv 2021年

作者： Chen, Yurong Zhang, Hui Wang, Yaonan Wu, Q. M. Jonathan Yang, Yimin National Engineering Laboratory of Robot Visual Perception and Control Technology School of Robotics Hunan University Hunan Changsha410082 China Department of Electrical and Computer Engineering University of Windsor WindsorONN9B3P4 Canada Department of Computer Science Lakehead University ONP7B 5E1 Canada Vector Institute TorontoONM5G 1M1 Canada

Anomaly detection refers to identifying the observation that deviates from the normal pattern, which has been an active research area in various domains. Recently, the increasing data scale, complexity, and dimension turns the traditional representation and statistical-based outlier detection method into challenging. In this paper, we leverage the generative model in hyperspectral images anomaly detection. The gist is to model the distribution of the normal data, while the out-of-distribution sample can be viewed as the outlier. At first, the variational inference-based anomaly detection methods are investigated. We theoretically and empirically find that they are unstable due to the strong notion of distance (f-divergence) served as the regularization. Secondly, this paper introduces sliced Wasserstein distance, which is a weaker distribution measure compared with f-divergence. However, the number of randomly slicing poses a difficulty to estimate the true distance. In the end, we propose a projected sliced Wasserstein (PSW) autoencoder-based anomaly screening method. In particular, we leverage a computation-friendly eigen-decomposition method to find the principal component as slicing the high-dimensional data. Furthermore, our proposed distance can be calculated with the closed-form, even the prior distribution is not Gaussian. Comprehensive experiments conducted on various real-world hyperspectral anomaly detection benchmarks demonstrate the superior performance of our proposed method. © 2021, CC BY.

关键词： Spectroscopy

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SMD classification system on PCB using two convolution neural networks

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Journal of Institute of control, robotics and Systems 2019年第10期25卷 923-928页

作者： Lim, Dae-Ui Kim, Young-Gyu Park, Tae-Hyoung Department of Control and Robot Engineering Chungbuk National University Korea Republic of School of Electronics Engineering Chungbuk National University Korea Republic of

It is important to classify SMD(Surface Mount Device) type for programing of AOI. A new SMD classification system is proposed using series of two CNNs to improve accuracy. A series of device region detection CNN and classification CNN are proposed where the first network is device region detect network and second network is device classification network. The device region detect network is designed lighter than the previously used region detect network. Experimental results showed that better accuracy is obtained when classification is performed after region detection. © ICROS 2019.

关键词： Printed circuit boards

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A lane detection and tracking method using image saturation and road width data

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Journal of Institute of control, robotics and Systems 2019年第5期25卷 476-483页

作者： Lee, Kang-Soo Heo, Sung-Woo Park, Tae-Hyoung Department of Control and Robot Engineering Chungbuk National University Korea Republic of School of Electronics Engineering Chungbuk National University Korea Republic of

It is necessary to have lane keeping system on autonomous vehicles. Recently vehicles with LKAS(Lane Keeping Assistance Sysyem) have been accomplished and are on sale, but only use on limited highway. Because highway is the easiest place to detect lane on the road. On the other hand, there are lots of road marking and curb on downtown region. In this paper we propose a robust lane detection and tracking method. The order of the proposed method is as follows. Firstly, calculate contrast of intensity and saturation to extract lane candidate. Secondly build the column histogram and find the lane region. Thirdly detecting both sides of lane and tracking lane using Kalman filter. As a result, the proposed system improves the detection accuracy and reduces computation time. Through various experiments, we show the robustness of the proposed system. © ICROS 2019.

关键词： Kalman filters

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Adaptive finite-time synchronized control of multi-robotic fiber placement system with model uncertainties and disturbances

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ISA Transactions 2025年

作者： Ronghua Zhang Yaonan Wang Wenfang Xie Pengcheng Li Haoran Tan Yiming Jiang College of Electrical and Information Engineering Hunan University Changsha 410082 Hunan China National Engineering Laboratory of Robot Visual Perception and Control Technology Hunan University Changsha 410082 Hunan China Department of Mechanical Industrial and Aerospace Concordia University Montreal H3G2W1 Quebec Canada College of Mechanical and Electrical Engineering Nanjing University of Aeronautics and Astronautics Nanjing 210016 Jiangsu China School of Robotics Hunan University Changsha 410082 Hunan China

The use of multiple robots to manufacture composite components represents a critical development direction for fiber placement systems (FPSs). In multi-robotic fiber placement systems (MRFPSs) with heterogeneous mechanical structures, robots collaborate to perform fiber placement tasks. Consequently, robot synchronization emerges as a primary factor in determining the performance of the fiber placement process. However, the difficulty in establishing accurate system models and the presence of disturbances are two significant challenges to achieving precise robot synchronization. Additionally, the system is expected to exhibit desirable dynamic characteristics, such as finite-time error convergence. To address these issues and requirements, we propose a novel adaptive finite-time synchronization control (AFSC) algorithm for the system. Specifically, a finite-time sliding mode observer is developed to handle kinematic uncertainty. A novel fast non-singular terminal sliding mode (FNTSM) manifold is constructed in the AFSC algorithm. Moreover, the control algorithm integrates an adaptive law to handle dynamic uncertainty and an adaptive term to counteract disturbances. Performance analysis demonstrates that the AFSC ensures that the coupled, synchronization, and tracking errors converge to zero within finite time. Furthermore, simulations and experiments are conducted to validate the effectiveness of the AFSC algorithm.

关键词： Disturbances Fiber placement Finite-time control Model uncertainties Multi-robots Synchronization control

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Real-time collision avoidance motion planning using vehicle lateral angular velocity constraints

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Journal of Institute of control, robotics and Systems 2019年第2期25卷 170-179页

作者： Heo, Sung-Woo Park, Tae Hyoung Department of Control and Robot Engineering Chungbuk National University Korea Republic of School of Electronics Engineering Chungbuk National University Korea Republic of

This paper proposes a method for motion planning of a vehicle considering lateral angular velocity constraints. Motion planning is very important for the safe travel of an autonomous vehicle. In this work, the steering angle of the vehicle is included in the cost function in order to achieve smooth operation of the vehicle. and path optimization uses dynamic programming to select the paths that satisfy the constraint with the least cost. After selecting the optimal path, the longitudinal velocity profile is determined using a fuzzy speed controller. The steering input of the vehicle and the distance from the obstacle to follow the path are used as the input of the fuzzy speed controller, and the controller provides longitudinal acceleration and deceleration of the vehicle as the output. Experiments were conducted for three scenarios using vehicles equipped with Lidar, IMU, GPS, and cameras. Experimental results show that the proposed motion plan generates a path within the steering constraint condition of the vehicle and runs effectively. © ICROS 2019.

关键词： Motion planning

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MyoPS: A Benchmark of Myocardial Pathology Segmentation Combining Three-Sequence Cardiac Magnetic Resonance Images

arXiv

引用

arXiv 2022年

作者： Li, Lei Wu, Fuping Wang, Sihan Luo, Xinzhe Martín-Isla, Carlos Zhai, Shuwei Zhang, Jianpeng Liu, Yanfei Zhang, Zhen Ankenbrand, Markus J. Jiang, Haochuan Zhang, Xiaoran Wang, Linhong Arega, Tewodros Weldebirhan Altunok, Elif Zhao, Zhou Li, Feiyan Ma, Jun Yang, Xiaoping Puybareau, Elodie Oksuz, Ilkay Bricq, Stephanie Li, Weisheng Punithakumar, Kumaradevan Tsaftaris, Sotirios A. Schreiber, Laura M. Yang, Mingjing Liu, Guocai Xia, Yong Wang, Guotai Escalera, Sergio Zhuang, Xiahai School of Data Science Fudan University Shanghai China School of Biomedical Engineering Shanghai Jiao Tong University Shanghai China Departament de Matemàtiques & Informàtica Universitat de Barcelona Barcelona Spain Computer Vision Center Universitat Autònoma de Barcelona Spain School of Mechanical and Electrical Engineering University of Electronic Science and Technology of China Chengdu China School of Computer Science and Engineering Northwestern Polytechnical University Xi'An China College of Electrical and Information Engineering Hunan University Changsha China National Engineering Laboratory for Robot Visual Perception and Control Technology Changsha China College of Physics and Information Engineering Fuzhou University Fuzhou China Comprehensive Heart Failure Center Wuerzburg University Hospitals Wuerzburg Germany School of Engineering University of Edinburgh Edinburgh United Kingdom School of Robotics Xi'an Jiaotong-Liverpool University Suzhou China Department of Electrical and Computer Engineering University of California Los Angeles United States Department of Radiology and Diagnostic Imaging University of Alberta Edmonton Canada Chongqing Key Laboratory of Image Cognition Chongqing University of Posts and Telecomm-Unications Chongqing China ImViA Laboratory Université Bourgogne Franche-Comté Dijon France Computer Engineering Department Istanbul Technical University Istanbul Turkey Le Kremlin-Bicêtre France Department of Mathematics Nanjing University of Science and Technology Nanjing China Department of Mathematics Nanjing University Nanjing China

Assessment of myocardial viability is essential in diagnosis and treatment management of patients suffering from myocardial infarction, and classification of pathology on myocardium is the key to this assessment. This work defines a new task of medical image analysis, i.e., to perform myocardial pathology segmentation (MyoPS) combining three-sequence cardiac magnetic resonance (CMR) images, which was first proposed in the MyoPS challenge, in conjunction with MICCAI 2020. The challenge provided 45 paired and pre-aligned CMR images, allowing algorithms to combine the complementary information from the three CMR sequences for pathology segmentation. In this article, we provide details of the challenge, survey the works from fifteen participants and interpret their methods according to five aspects, i.e., preprocessing, data augmentation, learning strategy, model architecture and post-processing. In addition, we analyze the results with respect to different factors, in order to examine the key obstacles and explore potential of solutions, as well as to provide a benchmark for future research. We conclude that while promising results have been reported, the research is still in the early stage, and more in-depth exploration is needed before a successful application to the clinics. Note that MyoPS data and evaluation tool continue to be publicly available upon registration via its homepage (***/zhuangxiahai/0/myops20/). © 2022, CC BY-NC-SA.

关键词： Magnetic resonance imaging

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Fully Stretchable, Porous Mxene-Graphene Foam Nanocomposites for Energy Harvesting and Self-Powered Sensing

SSRN

引用

SSRN 2022年

作者： Yang, Li Liu, Chaosai Yuan, Wenjing Meng, Chuizhou Dutta, Ankan Chen, Xue Guo, Langang Niu, Guangyu Cheng, Huanyu State Key Laboratory of Reliability and Intelligence of Electrical Equipment School of Health Sciences and Biomedical Engineering Hebei University of Technology Tianjin300130 China Tianjin Key Laboratory of Materials Laminating Fabrication and Interface Control Technology School of Materials Science & Engineering Hebei University of Technology Tianjin300130 China State Key Laboratory for Reliability and Intelligence of Electrical Equipment Hebei Key Laboratory of Smart Sensing and Human-Robot Interaction School of Mechanical Engineering Hebei University of Technology Tianjin300401 China Department of Engineering Science and Mechanics The Pennsylvania State University University Park 16802 United States State Key Laboratory of Reliability and Intelligence of Electrical Equipment Key Laboratory of Bioelectromagnetics and Neuroengineering of Hebei Province School of Electrical Engineering Hebei University of Technology Tianjin300130 China School of Architecture and Art Hebei University of Technology Tianjin300130 China

The growing demand for intelligent wearable electronic devices has spurred the rapid developments of high-performance deformable power supplies such as triboelectric nanogenerators (TENGs) with high output performance. However, the intrinsically stretchable TENGs especially those prepared with low-cost manufacturing approaches still suffer from poor performance. To address the challenge, this paper presents a fully stretchable TENG consisting of an intrinsically stretchable MXene/silicone elastomer and silver nanowires (Ag NWs)-graphene foam nanocomposite. The intrinsically stretchable TENG exhibits high output performance (voltage, current, and power of 73.6 V, 7.75 μA, and 2.76 W m -2 ), long-term reliability, and stable electrical output under various extreme deformation conditions. In addition to the application on the human skin and clothing for human motion monitoring and detecting the strength training postures, the intrinsically stretchable TENG can also harvest the intermittent mechanical energy from human bodies to charge various energy storage units such as commercial capacitors for driving wearable electronic devices. The resulting systems have been demonstrated in applications from home anti-theft to water resources early warning systems, which provide the proof-of-the-concept demonstrations for the next-generation standalone device platforms. © 2022, The Authors. All rights reserved.

关键词： Nanogenerators

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