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检索条件"机构=State Key Lab for Management and Control of Complex Systems"

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Underwater target search with robotic fish based on an improved Camshift algorithm

Underwater target search with robotic fish based on an impro...

引用

Chinese Automation Congress (CAC)

作者： Shifeng Chen Junzhi Yu Feihu Sun Min Tan State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing China

Biomimetic robotic fish has the distinct advantage of efficient propulsion and high maneuverability over conventional underwater vehicles. This paper addresses the underwater target search issue in a free-swimming robotic fish with embedded vision. In particular, we use the stored original image to acquire the color characteristics of the target and propose an improved Camshift algorithm based on the light intensity distribution to search the target in the captured image. Then the robotic fish is driven towards the identified target smoothly with the aid of bio-inspired Central Pattern Generator (CPG) control. All tracking algorithms are implemented in real time with a hybrid control system combining an embedded microprocessor (TI DM3730) and a microcontroller (ATmega128). Latest aquatic experiments demonstrate that a fairly good tracking effect is resulted and the interference caused by the mirror image effect is largely eliminated. The proposed technical scheme offers an alternative to target search in relatively complex underwater environments.

关键词： Marine animals Mirrors Robot kinematics Target tracking Image color analysis Microprocessors

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An enhanced dual-finger robotic Hand for Catheter manipulating in vascular intervention: A preliminary study

An enhanced dual-finger robotic Hand for Catheter manipulati...

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International Conference on Information and Automation (ICIA)

作者： Gui-Bin Bian Xiao-Liang Xie Zhen-Qiu Feng Zeng-Guang Hou Peng Wei Long Cheng Min Tan The State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing China

Cardiovascular disease is a class of diseases that involve the heart and blood vessels, which is the leading cause of deaths globally. Vascular interventional surgery is an effective treatment. As belongs to minimally invasive surgery (MIS), it is more popular due to the advantages of smaller injury, faster recovery and higher accuracy rate. However, it needs up to 10 years to train a skilled surgeon for minimally invasive cardiovascular surgeries. The surgeon cannot avoid receiving the excessive dose of X-ray due to long time operation in daily work. A dual-finger robotic hand (DRH) was introduced to assist the surgeon in manipulating the catheter/guide wire. As a surgical device, DRH is aiming at simple mechanism, ease to use and convenient sterilization. It was carefully investigated how the surgeon manipulates the catheter/guide wire. The bionic thumb and forefinger were designed to imitate human's. Compared to human's, the two bionic fingers are enhanced due to that they can advance the catheter/guide wire without moving the whole hand. The DRH mechanism was carefully designed. A console was also designed for the surgeon to manipulate DRH. After the DRH control was done, the minimum robotic cardiovascular interventional system was formed. Experimental results have validated the feasibility of DRH and the robotic system. Future work regarding DRH is also discussed.

关键词： Catheters Rubber Connectors Surgery Robots Couplers Transducers

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Robust mean-shift tracker with local saliency feature and spatial pattern preserved metric

Robust mean-shift tracker with local saliency feature and sp...

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International Conference on Mechatronic Science, Electric Engineering and Computer

作者： Linshan Liu Suiwu Zheng Hong Qiao Min Wang State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781479925667

Robust object tracking in crowded and cluttered dynamic scenes is a very difficult task in robotic vision due to complex and changeable environment and similar features between the background and foreground. In this paper, we present an improved mean-shift tracker which uses discriminative local saliency feature and a new spatial pattern preserved similarity metric method to overcome above difficulties in mean-shift based tracking approaches. The local saliency feature, which is composed of contrast color, texture and gradient around the target, is proposed to find the most distinguished features between the target and background, and it could enhance the tracking performance greatly in the cluttered and complex environment. Another important benefit of this feature is that the saliency map form could be easily embedded into the mean-shift framework. The new similarity metric try to preserve the spatial pattern to reduce the similarity errors caused by different spatial structure. It is beneficial to the mean-shift tracker to face the targets and scenes which has identical texture and color feature and with different spatial patterns. Finally, the efficiency of the proposed improved mean-shift tracker is validated through the plenty experimental results and analysis.

关键词： Target tracking Histograms Image color analysis Robustness Kernel Color

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Action Knowledge Extraction from Web Text

Action Knowledge Extraction from Web Text

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IEEE International Conference on Intelligence and Security Informatics

作者： Ansheng Ge Wenji Mao Daniel Zeng Lei Wang State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences

ISBN: (纸本)9781467362146

Action knowledge is an important type of behavioral knowledge and of vital importance to many applications in social computing, especially in behavior modeling, analysis and prediction. In this paper, we present a computational method to action knowledge extraction from online media. Our approach is based on mutual bootstrapping and combined with knowledge reasoning. Compared with the related work, our approach can acquire more types of action knowledge, and needs much less human labor. We evaluate the performance of our method using the Web textual data from security informatics domain. The experimental results show the effectiveness of our proposed method.

关键词： Action knowledge Knowledge extraction Bootstrapping Reasoning

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3D modeling of coronary arteries based on tubular-enhanced CURVES segmented regions for robotic surgical simulation

3D modeling of coronary arteries based on tubular-enhanced C...

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IEEE International Conference on Robotics and Biomimetics

作者： Fan Yang Zeng-Guang Hou Shao-Hua Mi Gui-Bin Bian Xiao-Liang Xie State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781479927456

The visualization of the coronary vasculature is of utmost importance in interventional cardiology. Intravascular surgical robots assist the practitioners to perform the complex procedure while protecting them from the tremendous occupational hazards. Robotic surgical simulation aims to provide support for the learners in both efficiency and convenience. The blood vessels especially the coronary arteries with rich details are the key part of the anatomic scenario of the virtual training system. The variations in diameters and directions make the segmentation of the coronary arteries a difficult work. In this paper, a robust and semi-automatic approach for the segmentation of the coronary arteries is developed. The approach is based on the multi-scale tubular enhancement and an improved geodesic active contours model. The demonstrated approach firstly enhances the tubular objects by computing their “vesselness”. Next the edge potential maps are calculated based on the enhanced information. Meanwhile, the initial contours are generated by a modified fast marching method. Then the actual wave fronts evolution extracts the details of the coronary arteries. Finally the visualization model is organized based on the segmentation results by the marching cubes method. This approach has been proved successful for the visualization of the coronary arteries based on the CTA information.

关键词： Arteries Robots Computational modeling Level set Eigenvalues and eigenfunctions Visualization Training

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EMG-based Estimation of Knee Joint Angle under Functional Electrical Stimulation Using an Artificial Neural Network

EMG-based Estimation of Knee Joint Angle under Functional El...

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第三十二届中国控制会议

作者： Yixiong Chen Jin Hu Feng Zhang Pengfeng Li Zengguang Hou State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences

ISBN: (纸本)9781479900305

In this paper,an artificial neural network is proposed to estimate knee joint angle in hybrid activation of knee extension motion,including voluntary muscle contraction and functional electrical stimulation(FES) induced *** electromyography(EMG) signals of three muscles responsible for knee extension and FES parameter which describe the FES intensity are used as input vector of the neural network,while the estimated knee angle is the *** the experiment, FES with different combinations of parameters(pulse amplitude and pulse width) was delivered to the rectus femoris muscle of a healthy male subject when the knee was in a periodic extension motion by voluntary muscle *** EMG signals of three muscles,parameters of FES as well as the actual knee angle were ***,there were 52,233 and 17,420 sampling points corresponding to 261 and 87 seconds used to train and validate the neural *** result shows the trained network has a satisfactory performance on knee joint angle estimation whose output well follows the curve of actual knee angle. Root mean square error between estimated angle and actual angle is employed to represent the estimation accuracy which is 5.07 degree according to the experimental data.

关键词： Functional electrical stimulation Electromyography Neural network

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Predicting User Participation in Social Networking Sites

Predicting User Participation in Social Networking Sites

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IEEE International Conference on Intelligence and Security Informatics

作者： Qingchao Kong Wenji Mao Daniel Zeng State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences

ISBN: (纸本)9781467362146

Social networking sites provide a convenient way for users to participate in discussion groups and communicate with others. While users situate in and enjoy such a social environment, it is important for various security related applications to understand, model and analyze participating users' behavior. In this paper, we make an attempt to model and predict user participation behavior in discussion groups of social networking sites. Our work employs a feature-based approach, which considers four types of features: thread features, content similarity, user behavior and social features. We conduct an empirical study on a popular social networking site in China, ***. The experimental results show the effectiveness of our approach.

关键词： User participation Behavior modeling and prediction Social networking sites

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Task-oriented active training based on adaptive impedance control with iLeg — A horizontal exoskeleton for lower limb rehabilitation

Task-oriented active training based on adaptive impedance co...

引用

IEEE International Conference on Robotics and Biomimetics

作者： Jin Hu Zeng-Guang Hou Yixiong Chen Liang Peng Long Peng State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781479927456

A horizontal exoskeleton for lower limb rehabilitation called iLeg has been developed by our laboratory which consists of two 3-DOF (degrees of freedom) robotic leg orthoses. This paper proposes a position-based impedance control with the compensation of BP NNs (back propagation neural networks) for the exoskeleton. Based on the control scheme, the task-oriented active training is investigated where impedance parameters are self-adjusted to movement deviation and patient activities with fuzzy logic. An adaptive haptic interface of active compliance is ensured to provide positive feedback to patients when their effort is desired or negative otherwise, which encourages patients to practice the desired movement following the predefined directed path. Besides, the timing freedom is separated from spatial trajectory and determined by patients. Voluntary effort hence becomes a requirement during the exercises, no effort no movement, so that active contribution of patients is highly motivated. Simulation results have verified the feasibility of the control scheme and the training strategy. An active compliant environment is created with adaptive haptic interface for task-oriented patient-driven training of multi-joint coordination.

关键词： Training Impedance Vectors Joints Robot kinematics Artificial neural networks

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Vehicle detection method based on active basis model and symmetry in ITS

Vehicle detection method based on active basis model and sym...

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2013 16th International IEEE Conference on Intelligent Transportation systems: Intelligent Transportation systems for All Modes, ITSC 2013

作者： Yao, Yanjie Gang, Xiong Wang, Kunfeng Zhu, Fenghua Wang, Fei-Yue State Key Laboratory of Management and Control for Complex Systems Beijing Engineering Research Center of Intelligent Systems and Technology Chinese Academy of Sciences Beijing 100190 China Dongguan Research Institute of CASIA Cloud Computing Center Chinese Academy of Sciences Dongguan China

ISBN: (纸本)9781479929146

Vehicle detection is a foundational and significant task in video surveillance systems. In this paper, a vehicle detection method using a deformable model and symmetry is proposed. First, we learn the active basis model (ABM) from the target training sample set by using the shared sketch algorithm. Then, we utilize the edge information obtained by ABM and HSV color information to do symmetry analysis for vehicle objects. The ABM can detect vehicles in various poses, shapes, and sizes for its deformability. By doing edge and color symmetry analysis, subtle difference between two images and environment noises can be adapted. The results of experiments indicate that our approach is capable of detection different vehicles and localization vehicle in bad environment. What's important, the detection results support the capability of the proposed method to enable the introduction of novel intelligent transportation systems applications. © 2013 IEEE.

关键词： Vehicles

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Target Tracking of Robotic Fish Based on Embedded Vision and CPG Model

Target Tracking of Robotic Fish Based on Embedded Vision and...

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IEEE International Conference on Information and Automation (ICIA)

作者： Sun, Feihu Yu, Junzhi Xu, De Wang, Ming Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Shandong Jianzhu Univ Sch Informat & Elect Engn Jinan 250101 Peoples R China

ISBN: (纸本)9781479913343

There has been greatly increased interest in using embedded vision for aquatic environments. This paper presents a robust target tracking method for a free-swimming biomimetic robotic fish by means of embedded vision and central pattern generator (CPG)-based motion control. Specifically, an algorithm called automatic continuous adaptive mean shift (Auto-CAMSHIFT) is firstly proposed to obtain the position and size of the interested target. Then a fuzzy logic controller is developed to generate the control input closely related to the desired target. A CPG controller that is robust against small and unexpected disturbance, at the same time, is employed to produce coordinated signals for multiple moving joints of the robotic fish. Finally, aquatic testing results verify the effectiveness of the proposed methods and show a satisfactory performance.

关键词： Embedded vision Central Pattern Generator (CPG) fuzzy logic control robotic fish

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