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IEEE International Conference on Robotics and Automation (ICRA)

作者： Zicong Wu Chuqian Lou Zhu Jin Shaoping Huang Ning Liu Yun Zou Mirko Kovac Anzhu Gao Guang-Zhong Yang Shanghai Jiao Tong University Shanghai P. R. China Imperial College London and Empa-Swiss Federal Laboratories for Materials Science and Technology Precision Robotics (Hong Kong) Limited Hong Kong China Aerial Robotics Laboratory Imperial College London London United Kingdom Shanghai Jiao Tong University and the Key Laboratory of System Control and Information Processing Ministry of Education Shanghai China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai China Institute of Medical Robotics Shanghai Jiao Tong University Shanghai P. R. China

Electrospinning has exhibited excellent benefits to treat the trauma for tissue engineering due to its produced micro/nano fibrous structure. It can effectively adhere to the tissue surface for long-term continuous therapy. This paper develops a robotic electrospinning platform for endoluminal therapy. The platform consists of a continuum manipulator, the electrospinning device, and the actuation unit. The continuum manipulator has two bending sections to facilitate the steering of the tip needle for a controllable spinning direction. Non-circular joint profile is carefully designed to enable a constant length of the centreline of a continuum manipulator for stable fluid transmission inside it. Experiments are performed on a bronchus phantom, and the steering ability and bending limitation in each direction are also investigated. The endoluminal electrospinning is also fulfilled by a trajectory following and points targeting experiments. The effective adhesive area of the produced fibre is also illustrated. The proposed robotic electrospinning shows its feasibility to precisely spread more therapeutic drug to construct fibrous structure for potential endoluminal treatments.

关键词： Drugs Electric potential Fluids Tissue engineering Medical treatment Bending Manipulators

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An Early Forest Fire Detection Method Based on Unmanned Aerial Vehicle Vision

An Early Forest Fire Detection Method Based on Unmanned Aeri...

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第30届中国控制与决策会议

作者： Sha Ma Youmin Zhang Jing Xin Yingmin Yi Ding Liu Han Liu Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology

Traditional forest fire detection methods based on flame are subject to detection delays due to the later appearrance of flame than smoke. When the flame is detected, the fire might have already been spread and out of ***, the objective of this paper is to study new fire detection method based on smoke. First a quadrotor unmanned aerial vehicle(UAV) is adopted to capture the fire video;then the collected video sequence will be processed by a series of preprocessing including filtering and image enhancement;finally a new significance detection algorithm is investigated for early and efficient smoke detection. Experimental results show that the algorithm can detect smoke effectively.

关键词： UAV vision Fire smoke Fire detection Significance detection algorithm

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Horizontal Positioning and Anti-swinging control Tower Crane Using Adaptive Sliding Mode control

Horizontal Positioning and Anti-swinging Control Tower Crane...

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第30届中国控制与决策会议

作者： Wen Wen Bai Hai-Peng Ren Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xian University of Technology

As a non-linear underactuated system, the tower crane should be controlled to transport the load to reference position quickly and smoothly. The actual tower crane is susceptible to the environment interference during operation. Conventional Proportion Integral Derivative（PID） controller cannot deal with this interference. Sliding mode control（SMC） is robust to system uncertainties and external disturbances, but it needs to know the upper bounds of uncertainties and external perturbations, which are usually unknown in practical systems. Adaptive backstepping sliding mode control（ABSMC） is used to adaptively estimate the uncertainties and external disturbances, and the stability of the system is proved based on Lyapunov theory. Compared with SMC, the proposed ABSMC has strong robustness.

关键词： tower crane Proportion Integral Derivative Sliding mode control Adaptive backstepping sliding mode control

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Research on Saturation of PMSM system Regulator for Electric Vehicle

Research on Saturation of PMSM System Regulator for Electric...

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Chinese Automation Congress (CAC)

作者： Shengmin Li Zeling Zhang Dan Zhao Siyu Guo Key Laboratory of Shaanxi Province for Complex System Control and Intelligent Information Processing Xi'an China

The saturation phenomenon often happens to the regulator in the start-up procedure of electric vehicles. And the dynamic and static performance of the motor will be worse while this phenomenon lasts longer. In this paper, firstly we will analyze the causes of this phenomenon, and then propose an effective method to solve the regulator saturation. Based on traditional double-loop vector control, this method increased the voltage cut-off negative feedback and combined the state feedback linearization to realize the dynamic decoupling between currents and solve the current regulator saturation problem which happens during start-up procedure. Finally, the feasibility and effectiveness of the proposed method were verified by simulation experiments, and the comprehensive performance of the motor, including speed range, speed tracking performance and dynamic response, was improved.

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Fault Diagnosis of SOFC Stack Based on Neural Network Algorithm

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Energy Procedia 2019年 158卷 1798-1803页

作者： Tao Xue Xiaolong Wu Yuanwu Xu Suwen Jing Zehua Li Jianhua Jiang Zhonghua Deng Xiaowei Fu Li Xi School of Automation Key Laboratory of Education Ministry for Image Processing and Intelligent Control Huazhong University of Science & Technology Wuhan 430074 China College of Computer Science and Technology Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan University of Science and Technology Wuhan 430065 China

To realize the commercialization of SOFC, it must be ensured that it can work efficiently and stably. SOFC fault diagnosis becomes an essential part of the research. Due to the strong coupling of faults in the stack, this paper uses neural network algorithm to detect and diagnose faults. The simulation results verify that through the diagnosis of the test sample, the recognition rate of the test sample by the network is found to be 95%, which explains the neural network fault diagnosis model established in this paper on identifying the normal working state of the stack, the electrode stacking of the stack, and the gas leakage fault of the stack has good effectiveness and accuracy.

关键词： SOFC fault diagnosis neural network

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ORB-Based Fast Anti-Viewing Image Feature Matching Algorithm

ORB-Based Fast Anti-Viewing Image Feature Matching Algorithm

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2018 Chinese Automation Congress, CAC 2018

作者： Oi, Liangliang Liu, Wei Liu, Ding Crystal Growth Equipment and System Integration Engineering Research Center Laboratory for Complex System Control and Intelligent of Information Processing Xi'An University of Technology Xi'an710048 China

ISBN: (纸本)9781728113128

Aiming at the problem that the original ORB algorithm is difficult to solve the effective matching problem under large angle of view transformation. This paper proposes an image feature matching algorithm based on ORB to resist the change of view according to the principle of ASIFT. The basic idea of the algorithm is as follows, Firstly, the longitude angle and latitude angle caused by the rotation of the camera are simulated, and the simulated image sequence set which is deformed by the change of the optical axis direction of the camera is accurately simulated. Then the feature points are extracted and mapped them into the original image by combining the FAST feature point detection method with the BRISK feature descriptors. Finally, the Brute-Force Matcher and the Random Sampling Consistency (RANSAC) method were used for feature matching and optimization. The experimental results show that the proposed algorithm can solve the problem that the image features cannot be matched under the large change of viewing angle (greater than 60°), and it has a significant improvement in real-time performance compared with ASIFT. © 2018 IEEE.

关键词： Cameras

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Multiple residual dense networks for reconfigurable intelligent surfaces cascaded channel estimation

arXiv

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arXiv 2021年

作者： Jin, Yu Zhang, Jiayi Huang, Chongwen Yang, Liang Xiao, Huahua Ai, Bo Wang, Zhiqin The School of Electronic and Information Engineering Beijing Jiaotong University Beijing100044 China The Frontiers Science Center for Smart High-speed Railway System Beijing Jiaotong University Beijing100044 China Zhejiang Provincial Key Lab of Information Processing Communication and Networking Zhejiang University Hangzhou310007 China College of Computer Science and Electronic Engineering Hunan University Changsha410082 China ZTE Corporation State Key Laboratory of Mobile Network Mobile Multimedia Technology Shenzhen518057 China State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing100044 China Henan Joint International Research Laboratory of Intelligent Networking and Data Analysis Zhengzhou University Zhengzhou450001 China Research Center of Networks and Communications Peng Cheng Laboratory Shenzhen518055 China China Academy of Information and Communications Technology Beijing100191 China

Reconfigurable intelligent surface (RIS) constitutes an essential and promising paradigm that relies programmable wireless environment and provides capability for space-intensive communications, due to the use of low-cost massive reflecting elements over the entire surfaces of man-made structures. However, accurate channel estimation is a fundamental technical prerequisite to achieve the huge performance gains from RIS. By leveraging the low rank structure of RIS channels, three practical residual neural networks, named convolutional blind denoising network, convolutional denoising generative adversarial networks and multiple residual dense network, are proposed to obtain accurate channel state information, which can reflect the impact of different methods on the estimation performance. Simulation results reveal the evolution direction of these three methods and reveal their superior performance compared with existing benchmark schemes. Copyright © 2021, The Authors. All rights reserved.

关键词： Channel estimation

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OpenHI2 - Open source histopathological image platform

OpenHI2 - Open source histopathological image platform

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2019 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2019

作者： Puttapirat, Pargorn Li, Chen Zhang, Haichuan Deng, Jingyi Dong, Yuxin Shi, Jiangbo He, Hongyu Gao, Zeyu Wang, Chunbao Zhang, Xiangrong Shaanxi Province Key Laboratory of Satellite and Terrestrial Network Tech. RD Xi'an Jiaotong University Xi'an Shaanxi710049 China Xi'an Jiaotong University Department of Software Engineering Xian Shaanxi710049 China School of Electrical Engineering Xi'an Jiaotong University Department of Power System and Automation Xi'an Shaanxi710049 China First Affiliated Hospital of Xi'an Jiaotong University Department of Pathology Xi'an Shaanxi710061 China Institute of Intelligent Information Processing Xidian University Xi'an Shaanxi710071 China

ISBN: (纸本)9781728118673

Transition from conventional to digital pathology requires a new category of biomedical informatic infrastructure which could facilitate delicate pathological routine. Pathological diagnoses are sensitive to many external factors and is known to be subjective. Only systems that can meet strict requirements in pathology would be able to run along pathological routines and eventually digitized the area, and the developed platform should comply with existing pathological routines and international standards. Currently, there are a number of available software tools which can perform histopathological tasks including virtual slide viewing, annotating, and basic image analysis, however, none of them can serve as a digital platform for pathology. Here we describe OpenHI2, an enhanced version Open Histopathological Image platform which is capable of supporting all basic pathological tasks and file formats;ready to be deployed in medical institutions on a standard server environment or cloud computing infrastructure. In this paper, we also describe the development decisions for the platform and propose solutions to overcome technical challenges including responsive region retrieval and viewing, virtual slide magnification, recording of diagnostic areas. These factors would promote OpenHI2 be used as a platform for histopathological images in real-world clinical settings. Furthermore, in research, OpenHI2 inherited the annotation functionality from the previous version, thus acquired annotations can be directly utilized by the newly added machine learning module which include popular machine learning models to perform tasks such as histology image classification and segmentation in the same environment. Addition can be made to the platform since each component is modularized and fully documented. OpenHI2 is free, open-source, and available at https://***/BioAI/OpenHI. © 2019 IEEE.

关键词： Open source software

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Structural Performance Analysis of Wall Climbing Robot 2

Structural Performance Analysis of Wall Climbing Robot

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2019 2nd International Conference on Advanced Materials, intelligent Manufacturing and Automation, AMIMA 2019

作者： Huang, Li Liao, Shangchun College of Computer Science and Technology Wuhan University of Science and Technology Wuhan Hubei430081 China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan University of Science and Technology Wuhan Hubei430081 China Key Laboratory of Metallurgical Equipment and Control Technology Ministry of Education Wuhan University of Science and Technology Wuhan Hubei430081 China

With the development of artificial intelligence technology, robotics technology has become more and more mature. Ground walking robots not only develop rapidly, but also have been applied in actual production and life. However, the development of wall climbing robot technology is still in the laboratory research and small-scale application. We live in a world where progress is continuing. Large-scale buildings, bridges and ships are becoming more and more common. In these places, it is inevitable to involve the construction, maintenance and clarity of high-rise buildings and ships. In the case of dangerous and inefficient manpower work, the application of wall climbing robots can play a very good role. Therefore, the development of wall climbing robots is of vital importance both now and in the future. Starting from the performance characteristics of wall climbing robot, this paper studies and summarizes the moving mode, control mode, conditions to be satisfied and various adsorption forms of wall climbing robot, and introduces the basic research situation in the field of wall climbing robot. © Published under licence by IOP Publishing Ltd.

关键词： Robot applications

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Vehicle detection based on point cloud intensity and distance clustering

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Journal of Physics: Conference Series 2021年第4期1748卷

作者： Zhao Wang Xing Wang Bin Fang Kun Yu Jie Ma School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan 430074 China National key laboratory of multispectral information processing technology Huazhong University of Science and Technology Wuhan 430074 China Science and technology on complex system control and intelligent agent cooperation laboratory Beijing 100074 China

In the intelligent transportation system, vehicle detection is one of the essential technologies in obstacle avoidance and navigation, however the existing vehicle detection methods cannot meet the actual needs. This paper presents a vehicle detection method combines the intensity and distance information of point cloud, which improves the segmentation performance of nearby objects. Specifically, the data of point cloud collected by lidar is preprocessed first. Then the processed point cloud is clustered by combining its coordinate and intensity information. Finally, the clustered suspected targets are fed to the random forest classifier. Our method can efficiently detect and classify targets in large-scale disordered 3D point cloud with high accuracy. In the real-scanned Livox Mid-40 Lidar dataset, our proposed method improves the detection accuracy by 31% compared with the traditional Euclidean clustering.

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