检索结果-内蒙古大学图书馆

自动化学报 2005年第3期31卷 427-433页

作者：邹玉兰汪国有张磊 Institute for Pattern Recognition and Artificial Intelligence State Education Commission Key Laboratory for Image Processing and Intelligent Control Huazhong University of Science & Technology Wuhan 430074

A fast object detection method based on object region dissimilarity and 1-D AGADM(one dimensional average gray absolute difference maximum) between object and background isproposed for real-time defection of small offshore targets. Then computational complexity, antinoiseperformance, the signal-to-noise ratio (SNR) gain between original images and their results as afunction of SNR of original images and receiver operating characteristic (ROC) curve are analyzed andcompared with those existing methods of small target detection such as two dimensional average grayabsolute difference maximum (2-D AGADM), median contrast filter algorithm and multi-level filteralgorithm. Experimental results and theoretical analysis have shown that the proposed method hasfaster speed and more adaptability to small object shape and also yields improved SNR performance.

关键词：小目标检测快速算法区域特性海面

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An agricultural data storage mechanism based on HBase

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International Journal of Information and Communication Technology 2019年第4期14卷 456-469页

作者： Li, Changyun Zhang, Qingqing He, Pinjie Wang, Zhibing Chen, Li College of Computer and Science Hunan University of Technology Zhuzhou412007 China Intelligent Information Perception and Processing Technology Hunan Province Key Laboratory Zhuzhou412007 China Intelligent Perception and Networked Control Hunan Province Key Laboratory of College Zhuzhou412007 China

With the development of agricultural space-Time localisation, sensor network and cloud computing, the amount of agricultural data is increasing rapidly and the data structure becomes more complicated and changeable. Currently, the widely used agricultural database is the relational database. This database handles a large amount of data with very limited throughput and is not suitable for organisation and management of distributed data. HBase is a non-relational database of distributed file storage built on Hadoop platform. HBase is suitable for unstructured data storage database and it can handle large volume of data with high scalability. To better store agricultural big data in HBase, we propose a special agricultural data buffer structure which stores data based on the data category and a two-level indexing memory organisation strategy on HBase. The method proposed saves more than a quarter of the time compared to traditional buffering methods. Experimental results show the higher efficiency of the agricultural data buffer structure and memory-organisation strategy. Copyright © 2019 Inderscience Enterprises Ltd.

关键词： Big data

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Optimal Ascent Guidance based on Direct Optimization Method

Optimal Ascent Guidance based on Direct Optimization Method

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2012 International Conference on Modelling,Identification and control(建模、辨别与控制国际会议 ICMIC 2012)

作者： Xuefang Lu Yongji Wang Candidate of Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Hu Key Laboratory of Ministry of Educationfor Image Processing and Intelligent Control Huazhong Univers

ISBN: (纸本)9781467315241

In this paper, an optimal guidance algorithm is proposed for atmospheric *** optimal guidance algorithm updates the reference trajectory to deal with the impact of disturbance by solving an optimal control problem *** the strong nonlinear ascent dynamic, the optimal control problem is transformed into nonlinear programming problem by trajectory *** direct optimization method is implemented for this nonlinear programming *** a segment of the reference trajectory is updated by the optimal guidance *** to the small amount of the discrete nodes and the initial guess solution which is close to the optimization solution, the direct optimization method is fast enough to generate a new reference *** simulation for the Generic Hypersonic Vehicle model and scramjet engine is done for different cases of the aerodynamic coefficient *** results show the accuracy and the effectiveness of this optimal guidance algorithm.

关键词： Optimal Guidance, Ascent, Direct Optimization

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USV Path Planning Based on ACO-SA Algorithm 42

USV Path Planning Based on ACO-SA Algorithm

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42nd Chinese control Conference, CCC 2023

作者： Luo, Chuanshang Tang, Yifeng Huang, Zhihui Xu, Yifan Liu, Bin Zhang, Hai-Tao School of Artificial Intelligence and Automation Huazhong University of Science and Technology The Engineering Research Center of Autonomous Intelligent Unmanned Systems The Key Laboratory of Image Processing and Intelligent Control The State Key Laboratory of Digital Manufacturing Equipment and Technology Wuhan430074 China

ISBN: (纸本)9789887581543

This paper solves USV path planning problem constrained by multiple factors via ant-colony optimization algorithm. First, this paper uses the ways of multi-objective optimization to model the USV path planning problem. An improved ant colony algorithm named ACO-SA is put forward afterwards to effectively solve the problem. The algorithm is a combination of ACO algorithm(ant colony algorithm) and SA algorithm(simulated annealing algorithm), which has three improments: change the initial distribution of pheromone to guide the search when the algorithm has just started running;change the heuristic function and state transition probability taking three factors into consideration;change the pheromone update rule and make the ants compete for the right to update pheromone by simulated annealing algorithm, and update the best solution by the same algorithm. Finally, simulation experiment and field experiment are conducted to check the validity of ACO-SA algorithm. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Simulated annealing

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An Improved High Precision 3D Semantic Mapping of Indoor Scenes from RGB-D images

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Computer Modeling in Engineering & Sciences 2023年第12期137卷 2621-2640页

作者： Jing Xin Kenan Du Jiale Feng Mao Shan Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi’an University of TechnologyXi’an710048China Australian Centre for Field Robotics The University of SydneySydney2006Australia

This paper proposes an improved high-precision 3D semantic mapping method for indoor scenes using RGB-D *** current semantic mapping algorithms suffer from low semantic annotation accuracy and insufficient real-time *** address these issues,we first adopt the Elastic Fusion algorithm to select key frames from indoor environment image sequences captured by the Kinect sensor and construct the indoor environment space ***,an indoor RGB-D image semantic segmentation network is proposed,which uses multi-scale feature fusion to quickly and accurately obtain object labeling information at the pixel level of the spatial point cloud ***,Bayesian updating is used to conduct incremental semantic label fusion on the established spatial point cloud *** also employ dense conditional random fields(CRF)to optimize the 3D semantic map model,resulting in a high-precision spatial semantic map of indoor *** results show that the proposed semantic mapping system can process image sequences collected by RGB-D sensors in real-time and output accurate semantic segmentation results of indoor scene images and the current local spatial semantic ***,it constructs a globally consistent high-precision indoor scenes 3D semantic map.

关键词： 3D semantic map online reconstruction RGB-D images semantic segmentation indoor mobile robot

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Soft Robotics:Morphology and Morphology-inspired Motion Strategy

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IEEE/CAA Journal of Automatica Sinica 2021年第9期8卷 1500-1522页

作者： Fan Xu Hesheng Wang Department of Automation Institute of Medical RoboticsKey Laboratory of System Control and Information Processing of Ministry of EducationShanghai Jiao Tong UniversityShanghai 200240China Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Jiao Tong UniversityShanghai 200240China

Robotics has aroused huge attention since the *** of the uniqueness that industrial applications exhibit,conventional rigid robots have displayed noticeable limitations,particularly in safe cooperation as well as with environmental ***,scientists have shifted their focus on soft robotics to apply this type of robots more effectively in unstructured *** decades,they have been committed to exploring sub-fields of soft robotics(e.g.,cutting-edge techniques in design and fabrication,accurate modeling,as well as advanced control algorithms).Although scientists have made many different efforts,they share the common goal of enhancing *** presented paper aims to brief the progress of soft robotic research for readers interested in this field,and clarify how an appropriate control algorithm can be produced for soft robots with specific *** paper,instead of enumerating existing modeling or control methods of a certain soft robot prototype,interprets for the relationship between morphology and morphology-dependent motion strategy,attempts to delve into the common issues in a particular class of soft robots,and elucidates a generic solution to enhance their performance.

关键词： Soft continuum manipulator soft gripper soft mobile robot soft robot control method soft robot modeling method soft robotics

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Remaining Useful Life Prediction for a Multi-stack Solid Oxide Fuel Cell System with Degradation Interactions

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CSEE Journal of Power and Energy Systems 2022年第4期8卷 1207-1214页

作者： Xiaojuan Wu Liangfei Xu Yang Huang Danan Yang Junhao Wang Houjun Wang Xi Li School of Automation Engineering University of Electronic Science and Technology of ChinaChengdu 610054China State Key Lab of Automotive Safety and Energy School of Vehicle and MobilityTsinghua UniversityBeijing 100084China School of Artificial Intelligencei and Automation Key Laboratory of Image Processing and Intelligent Control of Education MinistryHuazhong University of Science and TechnologyWuhan 430074China

Due to the constraints of manufacturing and materials,high-power plants cannot rely on only one solid oxide fuel cell stack.A multi-stack system is a solution for a highpower system,which consists of multiple fuel cell stacks.A short lifetime is one of the main challenges for the fuel cell before largescale commercial applications,and prognostic is an important method to improve the reliability of fuel *** from the traditional prognostic approaches applied to single-stack fuel cell systems,the key problem in multi-stack prediction is how to solve the correlation of multi-stack degradation,which can directly affect the accuracy of *** response to this difficulty,a standard Brownian motion is added to the traditional Wiener process to model the degradation of each stack,and then the probability density function of the remaining useful life(RUL)of each stack is ***,a Copula function is adopted to reflect the dependence between life distributions,so as to obtain the remaining useful life for the whole multi-stack system.1 The simulation results show that compared with the traditional prediction model,the proposed approach has a higher prediction accuracy for multi-stack fuel cell systems.

关键词： Degradation interaction multi-stack remaining useful life(RUL) solid oxide fuel cell(SOFC)

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Koopman Operator Learning control of the Piezoelectric Actuator 42

Koopman Operator Learning Control of the Piezoelectric Actua...

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42nd Chinese control Conference, CCC 2023

作者： Huang, Xiang Zhang, Hai-Tao School of Artificial Intelligence and Automation Huazhong University of Science and Technology Engineering Research Center of Autonomous Intelligent Unmanned Systems The Key Laboratory of Image Processing and Intelligent Control The State Key Laboratory of Digital Manufacturing Equipment and Technology Wuhan430074 China

ISBN: (纸本)9789887581543

The piezoelectric actuator is one kind of device that can drive nanoscale motion. However, the nonlinear hysteresis effect induced by its natural material greatly degrades its positioning accuracy. To handle this challenging issue, this work develops a Koopman model predict control (Koopman- MPC) framework for the piezoelectric actuator. Specifically, the Koopman operator theory is adapted for modeling the piezoelectric actuator dynamics. A simple yet powerful linear model spanned in a high-dimensional space is thus constructed to characterize the hysteresis dynamics. Subsequently, upon the established Koopman model, an MPC scheme is put forward for tracking control of piezoelectric actuators. Therein, by sustained optimizing a cost function containing future outputs and control increments, the control input is obtained. Moreover, extensive tracking simulations are carried out on a simulated piezoelectric actuator for verifying the feasibility and effectiveness of the Koopman- Mpc scheme. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Model predictive control

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WDNet: A Water Depth Perception Network with Global Information 42

WDNet: A Water Depth Perception Network with Global Informat...

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42nd Chinese control Conference, CCC 2023

作者： Huang, Zhihui Tang, Yifeng Tang, Chuancong Xu, Yifan Luo, Chuanshang Liu, Bin Zhang, Hai-Tao School of Artificial Intelligence and Automation The Engineering Research Center of Autonomous Intelligent Unmanned Systems The Key Laboratory of Image Processing and Intelligent Control The State Key Laboratory of Digital Manufacturing Equipment and Technology Huazhong University of Science and Technology Wuhan430074 China

ISBN: (纸本)9789887581543

Deep perception of the unmanned surface vehicle's surroundings is an inaccessible part of its fully autonomous navigation mission. The existing methods, whether based on traditional stereo matching or deep learning, do not fully consider the characteristics of water environment, resulting in severe error depths in weak textures (sky, calm lake) and water reflections regions, that increases the risk of running aground or collision. What is worse that there is not a public dataset for depth estimation in the water environment. Therefore, this work proposes a self-supervised model for depth estimation named Water Depth Perception Network (WDNet) to address these problems. The decoder of this network has a wider receptive field and can effectively handle the depth error in the weak texture region. Besides, the WDNet is trained with a novel and effective loss function which assist the network to reduce errors in sky and water region, and some indexes are proposed to evaluate the model's performances in sky and water region. Finally, our proposed WDNet achieves a 0.1056 absolute relative error in ranging, the average number of error pixels in the sky area drops from 15803.87 to 580.91, which only accounted for 0.29% of the image, and the error in water region drops from 51.04 to 6.75, all of them are superior to the performance of baseline model. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Errors

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Dynamic Graph Dismantling with Reinforcement Supervised Learning 42

Dynamic Graph Dismantling with Reinforcement Supervised Lear...

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42nd Chinese control Conference, CCC 2023

作者： Wang, Yumei Tang, Chuancong Zhang, Hai-Tao School of Artificial Intelligence and Automation Huazhong University of Science and Technology The Engineering Research Center of Autonomous Intelligent Unmanned Systems The Key Laboratory of Image Processing and Intelligent Control The State Key Laboratory of Digital Manufacturing Equipment and Technology Wuhan430074 China

ISBN: (纸本)9789887581543

There are always some 'key' nodes in a big complex network, which can joint the most connected subgraphs. How to identify these nodes, finding a minimum set of nodes to attack for reducing the size of residual network's Largest Connected Component(LCC) to break up the original network, has become a research hotspot. Therefore, a method for determining the 'key' nodes based on reinforcement learning framework and supervised learning model is proposed. This algorithm can not only utilize the dynamic exploration ability of reinforcement learning to collect a rich training dataset, but also take advantage of the characteristics that supervised learning is adaptive and has strong generalization ability to possess high efficiency and strong robustness. In order to further improve the algorithm's performance, ϵ-greedy mechanism is used to explore more network states. The experiment results show that given the same fraction of removed nodes, our algorithm can make the residual LCC smaller in various networks which is superior to the state-of-the-art algorithms in terms of effectiveness and generalization. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Complex networks

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