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IEEE International Conference on Cyber Technology in Automation, control, and intelligent systems

作者： Xuan Xiao Xiang Guo Yuan Liang Chao Shi Songtian Shang Hong Hu School of Automation and State Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology

ISBN: (纸本)9781538604915

Kalman filter has been extensively applied in vast areas. However, the performance of Kalman filter rests on the accuracy of prior information such as model construction. In the integrated system of Strapdown Inertial Navigation system (SINS)/Global Positioning system (GPS), the model construction is affected by a certain error sources. The most significant one is computational errors, which are caused by improper reference frame and the absence of true values. To solve the problem, this paper presents a modified system model which reduce the impact of computational errors by selecting computational frame as reference coordinate frame and removing all true values. Simulation results have demonstrated that modified system model effectively improves the performance of Kalman filter in SINS/GPS integrated system.

关键词： Kalman filters systems modelling Integrated system strapdown inertial navigation system Error Sources Modified

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Small-scale intersection scan model for UGV in urban environment

Small-scale intersection scan model for UGV in urban environ...

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American control Conference (ACC)

作者： Yi Yang Hao Li Hao Zhu Ningyi Lyu Wenjie Song School of Automation and State Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology Beijing Beijing CN School of Automation and State Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology Beijing China

Intersection detection is a critical capacity for an Unmanned Ground Vehicle (UGV) to drive safely in structured urban environment. Large-scale intersections stamped on maps have plenty of features for detection while some unmapped small-scale urban intersections are hard to be identified. In this paper, we propose a novel intersection detection method conducted on the basis of Hidden Markov Model (HMM). This method is based on the intersection scan model to obtain the traversable directions to classify the intersection. The scan model is effective in dealing with both LIDAR and visual data. Combination of the scan model and the HMM can accurately estimate the traversable directions in consideration of both real-time and historic data. Results from simulations and real-world experiments have shown the functionality of the presented approach.

关键词： Hidden Markov models Roads Global Positioning system Three-dimensional displays Urban areas Laser radar Autonomous vehicles

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UAV assisted bridge defect inspection system 3rd

UAV assisted bridge defect inspection system

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3rd International Conference on Intelligence Science, ICIS 2018

作者： Yang, Shuzhan Shen, Zhen Wang, Xiao Bai, Tianxiang Ji, Yingliang Jiang, Yuyi Liu, Xiwei Dong, Xisong Li, Chuanfu Han, Qi Lu, Jian Xiong, Gang State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China Qingdao Academy of Intelligent Industries Qingdao266109 China College of Engineering Peking University Beijing100871 China University of Chinese Academy of Sciences Beijing100049 China Cloud Computing Center Chinese Academy of Sciences Dongguan523808 China Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing100190 China Qingdao Expressway Qingdao266041 China Guangdong Launca Medical Device Technology Co. Ltd. Dongguan523808 China

ISBN: (纸本)9783030013127

Traditional bridge inspection methods require lane closures, inspection equipment, and most importantly the experiences and knowledge of the inspectors. This increases not only the inspection cost and time, but also the risk to the travelling public. Due to the lengthy and costly traditional bridge inspection methods, there has been an increasing backlog of inspection activities. In this research, we design an unmanned aerial vehicle (UAV) assisted bridge defect inspection system, in which a UAV can capture the image and transmit the information to the ground station for further analysis. The system can be divided into 2 subsystems: electromechanics & communication system, and image processing system. The electromechanics & communication systems ensure the self-locating, flight control, image transmission, and human intervention functions. The image processing system performs the image preprocessing, defect extraction, and provides the inspection report. This system, if put into practice, can save the cost up to 70%. We believe that the UAV assisted bridge inspection can be popular in the future. © IFIP International Federation for Information Processing 2018.

关键词： Image processing

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The 3D point clouds registration for human foot 3rd

The 3D point clouds registration for human foot

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3rd International Conference on Intelligence Science, ICIS 2018

作者： Xie, Yi Shang, Xiuqin Li, Yuqing Liu, Xiwei Zhu, Fenghua Xiong, Gang Pirttikangas, Susanna Zhou, Jiehan School of Electrical and Electronic Engineering The University of Manchester ManchesterM13 9PL United Kingdom The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China Cloud Computing Center Chinese Academy of Sciences DongguanGuangdong China College of Information Science and Technology Beijing University of Chemical Technology Beijing China Qingdao Academy of Intelligent Industries Qingdao China Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing100190 China The Center for Ubiquitous Computing University of Oulu Oulu Finland

ISBN: (纸本)9783030013127

For personalized design it is important to be able to collect, measure and evaluate individual properties of human beings. This paper proposes registration for the point clouds during foot 3D scanning. In the experiment, we get the point clouds of the human foot from the Artec 3D scanner and complete the registration of the point clouds from different visual angles. Dealing with the customized footwear, we choose a novel algorithm, which combines the NARF key point detector and the FPFH descriptor, to improve the efficiency of the initial iteration and reduce the computation burden of matching process. © IFIP International Federation for Information Processing 2018.

关键词： Iterative methods

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A new framework of science and technology innovation education for k-12 in Qingdao, China

A new framework of science and technology innovation educati...

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2017 ASEE International Forum

作者： Liu, Xiwei Gong, Xiaoyan Wang, Fei-Yue Sun, Rui Gao, Yanqing Zhang, Yu Zhou, Jiehan Deng, Xiaofei State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences China Intelligent Education Institution Qingdao Academy of Intelligent Industries China Qingdao Experimental High School China Oregon Institute of Technology United States University of Oulu Finland

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Automatic Safety Helmet Wearing Detection

Automatic Safety Helmet Wearing Detection

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IEEE International Conference on Cyber Technology in Automation, control, and intelligent systems

作者： Kang Li Xiaoguang Zhao Jiang Bian Min Tan The State Key Laboratory of Management and Control for Complex System University of Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781538604915

Surveillance is very essential for the safety of power substation. The detection of whether wearing safety helmets or not for perambulatory workers is the key component of overall intelligent surveillance system in power substation. In this paper, a novel and practical safety helmet detection framework based on computer vision, machine learning and image processing is proposed. In order to ascertain motion objects in power substation, the ViBe background modelling algorithm is employed. Moreover, based on the result of motion objects segmentation, real-time human classification framework C4 is applied to locate pedestrian in power substation accurately and quickly. Finally, according to the result of pedestrian detection, the safety helmet wearing detection is implemented using the head location, the color space transformation and the color feature discrimination. Extensive compelling experimental results in power substation illustrate the efficiency and effectiveness of the proposed framework.

关键词： Safety Substations Feature extraction Image color analysis Support vector machines Surveillance Classification algorithms

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An Adaptive INS/GPS/VPS Federal Kalman Filter for UAV Based on SVM

An Adaptive INS/GPS/VPS Federal Kalman Filter for UAV Based ...

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IEEE International Conference on Automation Science and Engineering

作者： Xuan Xiao Chao Shi Yi Yang Yuan Liang Xiang Guo School of Automation and State Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology Beijing China

In this paper, an adaptive modified federal Kalman filter is applied to the autonomous navigation with multi-sensors in condition that Unmanned Aerial Vehicle (UAV) is dynamically tracking Unmanned Ground Vehicle (UGV). To satisfy the autonomous navigation demands such as good accuracy, real time and high reliability for UAV, a new integrated navigation mode, in which Inertial Navigation system (INS) is aided by Global Position system (GPS)/Visual Positioning system (VPS), is proposed. Subsequently, a novel method is introduced which determined the information-sharing factors dynamically based on Singular Value Decomposition (SVD), and it not only solves the blindness of the information distribution factor of the conventional federated filter but also reduces the amount of calculation. According to the analysis of the theory about Support Vector Machine (SVM), an optimal objective kernel function is designed to select the effective source of information, thus it isolates the fault sensor. Simulation results show that the proposed integrated navigation system can provide abundant navigation information with sub-level navigation accuracy and good fault-tolerant performance. UAV can obtain reliable navigation information by this modified federal Kalman filter algorithm even when GPS or VPS is continuously interrupted for a period.

关键词： UGV UAV provide abundant

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Solutions Verification for Cloud-Based Networked control system using Karush-Kuhn-Tucker Conditions

Solutions Verification for Cloud-Based Networked Control Sys...

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Chinese Automation Congress

作者： Yasir Ali Zhen Shen Fenghua Zhu Gang Xiong Shichao Chen Yuanqing Xia Fei-Yue Wang The State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing China Cloud Computing Center Chinese Academy of Sciences Dongguan China School of Automation Beijing Institute of Technology China Beijing Engineering Research Center of Intelligent Systems and Technology Chinese Academy of Sciences Beijing China

The rapid development of the Cloud Computing Technologies (CCTs) has amended the conventional design of resource-constrained Network control system (NCS) to the powerful and flexible design of Cloud-Based Networked control system (CB-NCS) by relocating the processing part to the cloud server. This arrangement has produced many internets based exquisite applications. However, this new arrangement has also raised many network security challenges for the cloud-based control system related to cyber-physical part of the system. In the absence of robust verification methodology, an attacker can launch the modification attack in order to destabilize or take control of NCS. It is desirable that there shall be a solution authentication methodology used to verify whether the incoming solutions are coming from the cloud or not. This paper proposes a methodology used for the verification of the receiving solution to the local control system from the cloud using Karush-Kuhn-Tucker (KKT) conditions, which is then applied to actuator after verification and thus ensure the stability in case of modification attack.

关键词： Cloud-based control system Security of NCS Analysis of solution verification for NCS KKT conditions

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Parallel medical imaging for intelligent medical image analysis: Concepts, methods, and applications

arXiv

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arXiv 2019年

作者： Gou, Chao Shen, Tianyu Zheng, Wenbo Xue, Huadan Yu, Hui Ji, Qiang Jin, Zhengyu Wang, Fei-Yue School of Intelligent Systems Engineering Sun Yat-sen University Guangzhou510275 China The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China University of Chinese Academy of Sciences Beijing100049 China School of Software Engineering Xi’an Jiaotong University Xi’an710049 China Department of Radiology Peking Union Medical College Hospital Chinese Academy of Medical Sciences Peking Union Medical College Beijing100730 China School of Creative Technologies University of Portsmouth PortsmouthPO1 2DJ United Kingdom Department of Electrical Computer and Systems Engineering Rensselaer Polytechnic Institute Qingdao Academy of Intelligent Industries Qingdao266000 China

Data-driven artificial intelligence technologies have made much progress in medical image analysis in the last decades. However, it still remains challenging due to its distinctive complexity of acquiring and annotating image data, extracting medical domain knowledge, and explaining the diagnostic decision for medical image analysis. In this paper, we propose a data-knowledge-driven framework termed as Parallel Medical Imaging (PMI) for intelligent medical image analysis based on the methodology of interactive ACP-based parallel intelligence. In the PMI framework, computational experiments with predictive learning in a data-driven way are conducted to extract medical knowledge for diagnostic decision support. Artificial imaging systems are introduced to select and prescriptively generate medical image data in a knowledge-driven way to utilize medical domain knowledge. Through the closed-loop optimization based on parallel execution, our proposed PMI framework can boost the generalization ability and alleviate the limitation of medical interpretation for diagnostic decisions. Furthermore, we illustrate the preliminary implementation of PMI method through the case studies of mammogram analysis and skin lesion image analysis. Experimental results on several public medical image datasets demonstrate the effectiveness of proposed PMI. © 2019, CC BY.

关键词： Medical imaging

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A Real-time Hand Postures Estimation Method

A Real-time Hand Postures Estimation Method

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IEEE International Conference on Cyber Technology in Automation, control, and intelligent systems

作者： Sunjie Chen Hongbin Ma Cong Han School of Automation Beijing Institute of Technology State Key Laboratory of Complex System Intelligent Control and Decision Beijing 100081 China

ISBN: (纸本)9781538604915

Hand postures can be used to achieve friendly human-machine interaction (HMI) for the advantages of simple expressions, informative instructions and unconstrained operations. However, most previous postures estimation methods have problems such as poor real time performance, low estimation accuracy, being sensitive to the varying illumination and relying on marks on hands or special assistant devices. In this paper, we will introduce an efficient real-time method to estimate hand postures with an ordinary monocular camera. This method contains two stages, which are hand segmentation and postures recognition. Rather segment objects from the whole image, we locate the hand within a local area first and then adapt motion, color and contour informations to segment the hand region accurately. After that, template matching algorithm is used to recognize hand postures with fingertips and shape features. The experimental results demonstrated that the introduced method realizes high estimation accuracy and fast processing speed. Furthermore, the method is robust to varying illumination conditions.

关键词： Microsoft Windows Image segmentation Image color analysis Estimation Motion segmentation Support vector machines Lighting Motion segmentation image colour analysis Microsoft Windows(software) Lighting Hand body position Support Vector Network image segmentation Subdivision of hand

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