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Joint 48th IEEE Conference on decision and control and 28th Chinese control Conference

作者： Jing LI Junzheng WANG Bin ZHOU Wei SHEN Key Laboratory of Complex System Intelligent Control and Decision School of AutomationBeijing Institute of Technology

The CCD pixels nonuniformity may give a greater margin of error to measurement results in the high-precision CCD measurement and servo control *** paper analyzes the image pixels nonuniformity caused by noises,and establishes the corresponding image *** threshold value segmentation algorithm is used for image *** algorithm using two point linear method for pixel nonuniformity correction,getting center coordinates of facula by calculating the zeroth order moment and first moment of image is put forward,and a new image calibrated method that transforms the image coordinates into the real is *** results show that the algorithm can separate light intensity parts from the image,correct pixel nonuniformity,and stabilize pixel gray value of light intensity *** will make the center coordinates of image light intensity spots stable and decrease the error of the real coordinates after conversion,if the images are acquired under the same *** measurement precision as well as the control precision is improved greatly.

关键词： image Nonuniformity Correction and Calibration Method in the High-precision CCD Measurement and Servo control system CCD

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Magnetic Microrobots Fabricated by Photopolymerization and Assembly

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Cyborg and Bionic systems 2023年第1期4卷 41-46页

作者： Xiyue Liang Yue Zhao Dan Liu Yan Deng Tatsuo Arai Masaru Kojima Xiaoming Liu Key Laboratory of Biomimetic Robots and Systems Ministry of EducationState Key Laboratory of Intelligent Control and Decision of Complex SystemBeijing Advanced Innovation Center for Intelligent Robots and Systemsand School of Mechatronical EngineeringBeijing Institute of TechnologyBeijing 100081China Center for Neuroscience and Biomedical Engineering The University of Electro-CommunicationsTokyo 182-8585Japan Department of Materials Engineering Science Osaka UniversityOsaka 560-8531Japan

Magnetic soft microrobots have great potential to access narrow spaces and conduct multiple tasks in the biomedical *** now,drug delivery,microsurgery,disease diagnosis,and dredging the blocked blood vessel have been realized by magnetic soft microrobots in vivo or in ***,as the tasks become more and more complex,more functional units have been embedded in the body of the developed magnetic *** magnetic soft microrobots with complex designed geometries,mechanisms,and magnetic orientation are now greatly challenging the fabrication of the magnetic *** this paper,we propose a new method combining photopolymerization and assembly for the fabrication of magnetic soft *** the micro-hand assembly system,magnetic modules with different shapes and materials are firstly arrayed with precise position and orientation ***,the developed photopolymerization system is employed to fix and link these modules with soft *** on the proposed fabrication method,3 kinds of soft magnetic microrobots were fabricated,and the fundamental locomotion was *** believe that the presented fabrication strategy could help accelerate the clinical application of magnetic microrobots.

关键词： Magnetic system precise

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Object Tracking Algorithm of Adaptive Kernel-Bandwidth for Mean-Shift Based on Optical-flows

Object Tracking Algorithm of Adaptive Kernel-Bandwidth for M...

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第三十二届中国控制会议

作者： Qinlong He Junzheng Wang Jing Li Key Laboratory of Complex System Intelligent Control and Decision School of Automation Beijing Institute of Technology

ISBN: (纸本)9781479900305

To obtain and update the kernel-bandwidth,we present an adaptive bandwidth obtainment algorithm based on object contour extraction from optical-flow *** combination of modified mountain cluster approach and fast scanning window contour extractor guarantees the speed of this algorithm.A novel ellipse detection method based on a modified RANSAC is adopted to reduce the *** results demonstrate that the algorithm select the proper size of tracking kernel-bandwidth with minor extra computational overhead and keep up with the object robustly when the scale changed rapidly.

关键词： object tracking mean shift kernel bandwidth mountain cluster RANSAC

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A Map Matching Algorithm for Inertial Navigation systems Based on the Adaptive Projection Method

A Map Matching Algorithm for Inertial Navigation Systems Bas...

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International Symposium on Computational Intelligence and Design, ISCID

作者： Hao Luo Zhihong Deng Mengyin Fu Bo Wang National Key Laboratory of Intelligent Control and Decision of Complex System School of Automation Beijing China

ISBN: (纸本)9781479970063

In this paper, it studies the various elements of map-matching algorithm, in order to achieve better real-time and accuracy for vehicle navigation systems. This paper uses two-stage staggered mesh, combined with the second round screening domain. Using of vehicle location, direction, road geometric and topological relations with the angular rate of change, this paper proposes a new map matching algorithm, angle and distance segment dominated approach. The results show that the map-matching algorithm in this paper can achieve vehicle navigation and positioning functions accurately and quickly.

关键词： Roads Vehicles Navigation Accuracy Real-time systems Network topology Adaptive algorithms

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complex Terrain Perception based on Hidden Markov Model

Complex Terrain Perception based on Hidden Markov Model

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17th International IEEE Conference on intelligent Transportation systems & The Asia-Pacific Council on systems Engineering Conference 2014

作者： Meiling WANG Liang ZUO Yi YANG Qiangrong YANG Tong LIU School of Automation Beijing Institute of Technology Key Laboratory of Intelligent Control and Decision of Complex System

Terrain perception in complex environment is important for Autonomous Land Vehicle to drive *** order to access the terrain information,in this paper,we present a terrain perception method based on Hidden Markov Model(HMM) which combines LIDAR with machine *** the basis of spatial fan-shaped model,terrain feature extraction is performed to acquire the observation *** markov models describe the vertical structure of the driving space and Viterbi algorithm is used for terrain *** the navigation decision is given based on the perception of the complex *** results show that the method can give an accurate environment description for ALV.

关键词： terrain perception,sensor fusion,feature extraction,principal component analysis,multihidden markov models

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Cloud control systems

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自动化学报 2015年第2期2卷 134-142页

作者： Xia Yuanqing the School of Automation Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing 100081

The concept of cloud control systems is discussed in this paper, which is an extension of networked control systems (NCSs). With the development of internet of things (IOT), the technology of NCSs has played a key role in IOT. At the same time, cloud computing is developed rapidly, which provides a perfect platform for big data processing, controller design and performance assessment. The research on cloud control systems will give new contribution to the control theory and applications in the near future.

关键词： Cloud control systems (NCSs) networked control systems cloud computing cyber-physical systems (CPSs) big data

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ADFNet: A two-branch robotic grasping network based on attention mechanism

ADFNet: A two-branch robotic grasping network based on atten...

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第40届中国控制会议

作者： Pengwei Xie Nan Hao Bo Chen Beijing Institute of Technology School of Automation Key Laboratory of Complex System Intelligent Control and Decision

One of the challenges of RGB-D-based robotic grasping technology is how to make full use of these two complementary heterogeneous data sources while ensuring real-time performance. The existing robotic grasping methods mainly extract information from single-mode images or use a one-branch network to process RGB and depth images. These methods are insufficient in fully fusing the effective information of the two modes, which limits the anti-jamming performance. In this work,we propose Attention Dense Fusion Network（ADFNet）, a novel RGB-D based robotic grasping system that directly predicts the optimal grasping pose from RGB-D images. Our system uses a two-branch network with a heterogeneous framework that processes RGB and depth image information separately and retain the original structure of each data source. After applying dense fusion networks at different scales, the high-dimensional features in the RGB and depth branches are embedded and fused at the pixel level. Besides, we incorporate attention mechanisms to effectively suppress the independent background regions of the feature map and enhance the significant features, which improves the prediction accuracy. We conduct qualitative and quantitative experiments on the standard Cornell Grasp Dataset. The experimental results show that ADFNet can effectively improve the prediction accuracy to 98.9 %, which is better than existing methods while ensuing real-time performance.

关键词： robotic grasping RGB-D attention mechanism

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A multi-objective decomposition-based stochastic particle swarm optimization algorithm and its application to optimal design for linear motor

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Kongzhi Lilun Yu Yingyong/control Theory and Applications 2013年第6期30卷 693-701页

作者： Wang, Guang-Hui Chen, Jie Cai, Tao Li, Peng School of Automation Beijing Institute of Technology Beijing 100081 China Key Laboratory of Complex System Intelligent Control and Decision Ministry of Education Beijing 100081 China

This article proposes a multi-objective decomposition stochastic particle swarm optimization (MDSPSO) algorithm. In MDSPSO, every particle has a weighted vector constantly. Then, an improved Tchebycheff decomposition method is applied to decompose the multi-objective problem into some single-objective problems. The reference position of every particle is uniformly generated in the zone with the center which is the geometrical center of its current position, the best previous reference position as well as the swarm best reference position. The radius of this zone is the distance from the center to its current position. Then the particle is updated to the new position according to the reference position and its current velocity. The comparisons with the decomposition-based multi-objective particle swarm optimizer (dMOPSO), a multiobjective evolutionary algorithm based on decomposition (MOEA/D), and nondominated sorting genetic algorithm II (NSGA-II) show that the solutions of MDSPSO can be dominated at least with the best diversity. To reduce the computational time by finite element analysis for optimizing the structure parameters of linear motor, artificial neural network is used as the model to evaluate the performance. Finally, MDSPSO is applied to optimize four objectives simultaneously. The practical result is shown that the optimized linear motor has an increased thrust, improved efficiency, reduced fluctuation and manufacturing cost.

关键词： Multiobjective optimization

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An attention-based RGBD dual-branch gesture recognition network

An attention-based RGBD dual-branch gesture recognition netw...

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第40届中国控制会议

作者： Bo Chen Pengwei Xie Nan Hao Beijing Institute of Technology School of Automation Key Laboratory of Complex System Intelligent Control and Decision

In this work,we use a hierarchical architecture based on detector-classifier for gesture recognition *** the operation of the architecture,the detector,which is essentially the switch of the classifier,is always *** the output of the detector is true,then the classifier is activated and returns a classification label for the input video *** work focuses on the improvement of detectors and *** the detector,we introduce an attention mechanism to guide the network to focus on the space and channel where the gesture is *** the classifier,based on the RGB information stream,we use an independent branch to extract the features of the depth stream,and finally merge the two *** gestures move in a three-dimensional space,depth information can make up for the lack of RGB *** show that on the Egogesture test set,our detector achieves 98.86% accuracy on RGB input,while the classifier achieves 93.85% *** the same time,our gesture recognition architecture can fully meet the real-time requirements.

关键词： Gesture Recognition RGBD feature fusion attention mechanism real-time

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Dynamic collision avoidance for cooperative fixed-wing UAV swarm based on normalized artificial potential field optimization

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Journal of Central South University 2021年第10期28卷 3159-3172页

作者： LIU Wei-heng ZHENG Xin DENG Zhi-hong State Key Laboratory of Intelligent Control and Decision of Complex Systems School of AutomationBeijing Institute of TechnologyBeijing 100081China China Aerospace Science and Industrial Corporation Beijing 100048China

Cooperative path planning is an important area in fixed-wing UAV ***,avoiding multiple timevarying obstacles and avoiding local optimum are two challenges for existing approaches in a dynamic ***,a normalized artificial potential field optimization is proposed by reconstructing a novel function with anisotropy in each dimension,which can make the flight speed of a fixed UAV swarm independent of the repulsive/attractive gain coefficient and avoid trapping into local optimization and local ***,taking into account minimum velocity and turning angular velocity of fixed-wing UAV swarm,a strategy of decomposing target vector to avoid moving obstacles and pop-up threats is ***,several simulations are carried out to illustrate superiority and effectiveness.

关键词： fixed-wing UAV swarm cooperative path planning normalized artificial potential field dynamic obstacle avoidance local optimization

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