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检索条件"机构=Sate Key Laboratory of Management and Control for Complex Systems"

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Fast Rejecting Mismatches Using Pair-wise Similarity

Fast Rejecting Mismatches Using Pair-wise Similarity

引用

World Congress on Intelligent control and Automation

作者： Deheng Qian Xu Yang Yuren Zhang Hong Qiao State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences

ISBN: (纸本)9781467384155

Point matching problem seeks the optimal correspondences between two sets of points. However, the matching result often includes some mismatches that decrease the matching precision. In this paper, we propose a fast algorithm to reject mismatches using pair-wise similarity. The intuition of our algorithm is that the matches should be similar with their neighboring matches due to local consistency. Our algorithm consists of two steps. In the first step, the algorithm eliminates mismatches at the cost of rejecting some correct matches to obtain a refined matching result with a high precision. In the second step, the algorithm regains the correct matches rejected in the first step to improve the recall of the final matching result. The time complexity of the algorithm is O(n~2), which is asymptotically faster than conventional algorithms that reject mismatches. We demonstrate the effectiveness of the proposed algorithm by multiple experiments over widely used datasets.

关键词： MISMATCH complexity classes algorithms recall Mental Recall

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Parallel control and management system for biomimetic robotic fish based on ACP approach

Parallel control and management system for biomimetic roboti...

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World Congress on Intelligent control and Automation (WCICA)

作者： Jincun Liu Zhengxing Wu Xiang Yang Junzhi Yu State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781467384155

This paper deals with the management and control of a biomimetic robotic fish within a control framework of artificial systems, computational experiments, and parallel execution (ACP). Without the need of precise hydrodynamic modeling and control implementation, we firstly built a functionally equivalent artificial robotic fish by using the Agent technology. When performing a specific task, network-stored control strategies and environment models can be downloaded for computing, testing, and optimizing purposes. By parallel execution, the optimal algorithm can be transferred to the physical robotic fish, where error feedback signals serve to seek the optimal solution in the network. Furthermore, the optimized control strategies, environment models, as well as the newly learned knowledge will be uploaded to the network after accomplishing the mission. At last, we demonstrate this ACP-centered control method through pushball experiment on robotic fish.

关键词： Fish Robot sensing systems Computational modeling Robot kinematics control systems Biological system modeling

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sEMG-based Prediction of Human Lower Extremity Movements by Using a Dynamic Recurrent Neural Network

sEMG-based Prediction of Human Lower Extremity Movements by ...

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第28届中国控制与决策会议

作者： Chengkun Cui Gui-Bin Bian Zeng-Guang Hou Xiao-Liang Xie Liang Peng Dongxu Zhang The State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences

ISBN: (纸本)9781467397155

In this paper,a novel robust nonlinear model is proposed to predict human lower extremity motion based on the multi-channel surface electromyography(sE MG) *** prediction model is established by a data-driven dynamic recurrent neural *** sE MG signals acquired from human lower extremity muscles are used as the inputs of the prediction *** outputs of the model are joint angles of hip,knee and *** from the traditional feedforward network structure,this model has several feedback loops,thus it can take advantage of the output feedback *** validate the effectiveness of the proposed method,five able-bodied people participated in the cycling exercises and relevant data were recorded in real *** performance of the proposed prediction model is compared to those of the feedforward neural network with augmented inputs(FFNNAI) for the motion prediction accuracy and *** results show that the proposed method provides acceptable performance which is clearly better than the FFNNAI-based approach under different experimental schemes.

关键词： sEMG motion prediction dynamic recurrent neural networks human-robot interaction

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Overview of deep learning

Overview of deep learning

引用

Youth Academic Annual Conference of Chinese Association of Automation (YAC)

作者： Xuedan Du Yinghao Cai Shuo Wang Leijie Zhang The State Key Laboratory of Management and Control for Complex Systems Institute of Automation CAS Beijing China

ISBN: (纸本)9781509044245

In recent years, deep learning has achieved great success in many fields, such as computer vision and natural language processing. Compared to traditional machine learning methods, deep learning has a strong learning ability and can make better use of datasets for feature extraction. Because of its practicability, deep learning becomes more and more popular for many researchers to do research works. In this paper, we mainly introduce some advanced neural networks of deep learning and their applications. Besides, we also discuss the limitations and prospects of deep learning.

关键词： Decision support systems Erbium Recurrent neural networks

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Travel Time Prediction with LSTM Neural Network

Travel Time Prediction with LSTM Neural Network

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IEEE International Conference on Intelligent Transportation systems

作者： Yanjie Duan Yisheng Lv Fei-Yue Wang The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences

ISBN: (纸本)9781509018901

Travel time is one of the key concerns among travelers before starting a trip and also an important indicator of traffic conditions. However, travel time acquisition is time delayed and the pattern of travel time is usually irregular. In this paper, we explore a deep learning model, the LSTM neural network model, for travel time prediction. By employing the travel time data provided by Highways England, we construct 66 series prediction LSTM neural networks for the 66 links in the data set. Through model training and validation, we obtain the optimal structure within the setting range for each link. Then we predict multi-step ahead travel times for each link on the test set. Evaluation results show that the 1-step ahead travel time prediction error is relatively small, the median of mean relative error for the 66 links in the experiments is 7.0% on the test set. Deep learning models considering sequence relation are promising in traffic series data prediction.

关键词： Travel time Travelers relative errors Traffic Model trains Neural network TEST SETS

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Design of a camera stabilizer system for robotic fish based on feedback-feedforward control

Design of a camera stabilizer system for robotic fish based ...

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Chinese control Conference (CCC)

作者： Xiang Yang Zhengxing Wu Jincun Liu Junzhi Yu State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing P. R. China State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing Beijing CN

This paper presents a novel approach for a visual system of robotic fish to reduce the instability of camera image caused by the inherent periodic yawing of the fish head. In order to acquire the stable image from the camera located inside of the fish head, a camera stabilizer for the visual system is designed. Meanwhile, an Inertial Measurement Unit (IMU) with nine degrees-of-freedom (DoFs) is employed to maintain the attitude of the camera stable with respect to the inertial frame. To accurately describe the stabilizer system characteristics, a simple and effective system model is built. Moreover, a feedback-feedforward controller is proposed to mitigate the periodic swing effect and obtain stable and clear camera image when the robotic fish is swimming. Finally, the simulation and experiments both verified the effectiveness of the mechanism design for camera stabilizer and the corresponding feedback-feedforward control approach for enhancing the stability of images.

关键词： Cameras Robot vision systems control systems Head Feedforward neural networks

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A Slope Detection Method Based on 3D LiDAR Suitable for Quadruped Robots

A Slope Detection Method Based on 3D LiDAR Suitable for Quad...

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World Congress on Intelligent control and Automation

作者： Xiangrui Meng Zhiqiang Cao Leijie Zhang Shuo Wang Chao Zhou State Key Laboratory of Management and Control for Complex Systems Institute of Automation CAS Beijing 100190 China

ISBN: (纸本)9781467384155

This paper introduces a slope detection method based on point cloud data from 3D LiDAR for quadruped robots in unknown environments. For quadruped robots, they need to adjust their gaits according to different slope angles to avoid some potential dangers. 3D LiDAR is used to gather point cloud data, which is superior to 2D LiDAR in speed and accuracy. In this paper, a slope detection method using bilateral filtering and RANSAC algorithms is discussed. The experiments of slope detection are fulfilled with the consideration of different angles of slopes and different orientations to the slopes, and the results demonstrate that errors of angle estimation is small.

关键词： Laser radar Three-dimensional displays Robot kinematics Robot sensing systems Mobile robots Lidar quadruped robot three-dimensional displays Manipulator sensing systems Robot kinematics Mobile robots bilateral filtering Unknown environments

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Hydrodynamic analysis of a gliding robotic dolphin based on Computational Fluid Dynamics

Hydrodynamic analysis of a gliding robotic dolphin based on ...

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Chinese control Conference (CCC)

作者： Kang Li Junzhi Yu Zhengxing Wu Min Tan State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing Beijing CN

ISBN: (纸本)9781509009107

This paper presents a concrete and practical hydrodynamic analysis for a hybrid gliding robotic dolphin. In order to obtain the accurate hydrodynamic performance of both dolphin-like swimming and gliding motion, a Computational Fluid Dynamics (CFD) method is employed. Specifically, based on the FlUENT dynamic mesh interface, a novel dynamic mesh and user-defined function (UDF) are developed to describe the dorsoventral oscillations of the dolphin. Besides, the corresponding turbulent model and SIMPLE algorithm suited to dolphin-like swimming are also meticulously selected for great accuracy and high quality. Finally, the FLUENT simulation results reveal the pressure distribution and velocity field distribution around the robotic dolphin. Moreover, some important hydrodynamic coefficients including lift coefficients and drag coefficients at different frequencies are also obtained. The simulation results illustrate an expected hydrodynamic performance of the gliding robotic dolphin.

关键词： Dolphins Hydrodynamics Mathematical model Robot kinematics Computational modeling

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A 3-DOF compact haptic interface for endoscopic endonasal approach surgery simulation

A 3-DOF compact haptic interface for endoscopic endonasal ap...

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IEEE/ASME (AIM) International Conference on Advanced Intelligent Mechatronics

作者： Jianlong Hao Gui-Bin Bian XiaoLiang Xie Zeng-Guang Hou Xiao-Hu Zhou State Key Laboratory of Management and Control for Complex Systems University of Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781509020669

Endoscopic endonasal approach surgery is now the preferred treatment for most pituitary and related skull base tumors. However, this procedure requires a high level of hands-on skills and rich clinical experience. During the operation, haptic feedback, as the only one sense of bidirectional information interaction, plays an important role in surgical decision-making especially for bone-drilling. Existing surgical simulators provide either no haptic device or multipurpose haptic devices, which is difficult to reproduce the characteristics of surgical tool handling. In this paper, a custom-designed 3-DOF (pitch, yaw, radial) compact haptic interface for this surgery simulation is presented. It is dedicated to mimicking the touch sense of the surgical tools inserted through the nostril. Its main innovation is the mechanism design to maintain as much fidelity of the tool handling in the surgical training as in a real operation. The mechanism design is presented in detail as well as the kinematics and the force transmission. The mechanical characteristics of this haptic interface are also analyzed and presented.

关键词： Haptic interfaces Rails Force Training Neurosurgery Skull

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Deep reinforcement learning with experience replay based on SARSA

Deep reinforcement learning with experience replay based on ...

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IEEE Symposium Series on Computational Intelligence (SSCI)

作者： Dongbin Zhao Haitao Wang Kun Shao Yuanheng Zhu Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781509042418

SARSA, as one kind of on-policy reinforcement learning methods, is integrated with deep learning to solve the video games control problems in this paper. We use deep convolutional neural network to estimate the state-action value, and SARSA learning to update it. Besides, experience replay is introduced to make the training process suitable to scalable machine learning problems. In this way, a new deep reinforcement learning method, called deep SARSA is proposed to solve complicated control problems such as imitating human to play video games. From the experiments results, we can conclude that the deep SARSA learning shows better performances in some aspects than deep Q learning.

关键词： Learning (artificial intelligence) Games Training Neural networks Machine learning Feature extraction

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