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arXiv 2019年

作者： Mu, Biqiang Qi, Hongsheng Petersen, Ian R. Shi, Guodong Key Laboratory of Systems and Control Institute of Systems Science Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China Research School of Electrical Energy and Materials Engineering Australian National University Canberra0200 Australia Australian Center for Field Robotics School of Aerospace Mechanical and Mechatronic Engineering University of Sydney 2008 Australia

In this paper, we study extended linear regression approaches for quantum state tomography based on regularization techniques. For unknown quantum states represented by density matrices, performing measurements under certain basis yields random outcomes, from which a classical linear regression model can be established. First of all, for complete or over-complete measurement bases, we show that the empirical data can be utilized for the construction of a weighted least squares estimate (LSE) for quantum tomography. Taking into consideration the trace-one condition, a constrained weighted LSE can be explicitly computed, being the optimal unbiased estimation among all linear estimators. Next, for general measurement bases, we show that '2-regularization with proper regularization gain provides even lower mean-square error under a cost in bias. The regularization parameter is tuned by two estimators in terms of a risk characterization. Finally, a concise and unified formula is established for the regularization parameter with complete measurement basis under an equivalent regression model, which proves that the proposed tuning estimators are asymptotically optimal as the number of samples grows to infinity under the risk metric. Additionally, numerical examples are provided to validate the established results. Copyright © 2019, The Authors. All rights reserved.

关键词： Tomography

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Measurement-induced boolean dynamics and controllability for quantum networks

arXiv

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arXiv 2019年

作者： Qi, Hongsheng Muy, Biqiang Petersenz, Ian R. Shix, Guodong Key Laboratory of Systems and Control Institute of Systems Science Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China Research School of Electrical Energy and Materials Engineering Australian National University Canberra0200 Australia Australian Center for Field Robotics School of Aerospace Mechanical and Mechatronic Engineering University of Sydney NSW2008 Australia

In this paper, we study dynamical quantum networks which evolve according to Schrodinger equations but subject to sequential local or global quantum measurements. A network of qubits forms a composite quantum system whose state undergoes unitary evolution in between periodic measurements, leading to hybrid quantum dynamics with random jumps at discrete time instances along a continuous orbit. The measurements either act on the entire network of qubits, or only a subset of qubits. First of all, we reveal that this type of hybrid quantum dynamics induces probabilistic Boolean recursions representing the measurement outcomes. With global measurements, it is shown that such resulting Boolean recursions define Markov chains whose state-transitions are fully determined by the network Hamiltonian and the measurement observables. Particularly, we establish an explicit and algebraic representation of the underlying recursive random mapping driving such induced Markov chains. Next, with local measurements, the resulting probabilistic Boolean dynamics is shown to be no longer Markovian. The state transition probability at any given time becomes dependent on the entire history of the sample path, for which we establish a recursive way of computing such non-Markovian probability transitions. Finally, we adopt the classical bilinear control model for the continuous Schrodinger evolution, and show how the measurements affect the controllability of the quantum networks. Copyright © 2019, The Authors. All rights reserved.

关键词： Quantum optics

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Measurement-Induced boolean dynamics for open quantum networks

arXiv

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arXiv 2019年

作者： Qi, Hongsheng Mu, Biqiang Petersen, Ian R. Shi, Guodong Key Laboratory of Systems and Control Institute of Systems Science Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China Research School of Electrical Energy and Materials Engineering Australian National University Canberra0200 Australia Australian Center for Field Robotics School of Aerospace Mechanical and Mechatronic Engineering University of Sydney NSW2008 Australia

In this paper, we study the recursion of measurement outcomes for open quantum networks under sequential measurements. Open quantum networks are networked quantum subsystems (e.g., qubits) with the state evolutions described by a continuous Lindblad master equation. When measurements are performed sequentially along such continuous dynamics, the quantum network states undergo random jumps and the corresponding measurement outcomes can be described by a vector of probabilistic Boolean variables. The induced recursion of the Boolean vectors forms a probabilistic Boolean network. First of all, we show that the state transition of the induced Boolean networks can be explicitly represented through realification of the master equation. Next, when the open quantum dynamics is relaxing in the sense that it possesses a unique equilibrium as a global attractor, structural properties including absorbing states, reducibility, and periodicity for the induced Boolean network are direct consequences of the relaxing property. Particularly, we show that generically, relaxing quantum dynamics leads to irreducible and aperiodic chains for the measurement outcomes. Finally, we show that for quantum consensus networks as a type of non-relaxing open quantum network dynamics, the communication classes of the measurement-induced Boolean networks are encoded in the quantum Laplacian of the underlying interaction graph. Copyright © 2019, The Authors. All rights reserved.

关键词： Quantum theory

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Automatic Cell Assembly by Two-fingered Microhand

Automatic Cell Assembly by Two-fingered Microhand

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2019 IEEE/RSJ International Conference on Intelligent Robots and systems (IROS)

作者： Junnan Chen Xiaoming Liu Shengnan Dong Pengyun Li Xiaoqing Tang Dan Liu Masaru Kojima Qiang Huang Tatsuo Arai Intelligent Robotics Institute School of Mechatronical Engineering Key Laboratory of Biomimetic Robots and Systems Ministry of Education Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology Beijing CHINA Department of Systems Innovation Graduate school of Engineering Science Osaka University Toyonaka Osaka Japan Global Alliance Lab The University of Electro-Communications Tokyo Japan

We have successfully achieved manipulation and assembly of microbeads having the size of 100μm diameter by hemispherical end-effectors with high stability and accuracy. The motivation of achieving assembly of actual cells lies in the great significance of it in tissue regeneration and cell analysis. Firstly, the most difficult problem we need to solve is the releasing problem caused by adhesion force. The viscosity on cell surface is much larger than the microbeads which makes cell releasing challenging. Secondly, the cell can generate its deformation, then contact area with end-effector will change during grasping process. This may influence the adhesion force and also bring problem to releasing. Thirdly, cell is much smaller, around 15μm in diameter, so we need to fabricate smaller end-effector to achieve successful manipulation and ensure the stability in the meantime. In this paper, we realize the manipulation by decreasing the adhesion forces and apply vibration to release a cell stably. We found the appropriate scale size for the end-effector is around 10μm diameter. It can not only grasp a 15μm cell but also bring little interference to the environment. As a demonstration of the proposed manipulation method, the repeated experiments were conducted to explore the dependence of adhesion force on the grasping distance, which can be helpful in the improvement of successful rate. Finally, we achieved automatic cell assembly using Hela cells.

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Data Cleaning Based on Multi-sensor Spatiotemporal Correlation 4th

Data Cleaning Based on Multi-sensor Spatiotemporal Correlati...

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4th International Conference on Machine Learning and Intelligent Communications, MLICOM 2019

作者： Shao, Baozhu Song, Chunhe Wang, Zhongfeng Li, Zhexi Yu, Shimao Zeng, Peng Liaoning Electric Power Research Institute State Grid Liaoning Electric Power Co. Ltd. 110000 Shenyang China Key Laboratory of Networked Control Systems Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110016 China Shenyang Power Supply Company State Grid Liaoning Electric Power Co. Ltd. 110000 Shenyang China

ISBN: (纸本)9783030323875

Sensor-based condition monitoring systems are becoming an important part of modern industry. However, the data collected from sensor nodes are usually unreliable and inaccurate. It is very critical to clean the sensor data before using them to detect actual events occurred in the physical world. Popular data cleaning methods, such as moving average and stacked denoise autoencoder, cannot meet the requirements of accuracy, energy efficiency or computation limitation in many sensor related applications. In this paper, we propose a data cleaning method based on multi-sensor spatiotemporal correlation. Specifically, we find out and repair the abnormal data according to the correlation of sensor data in adjacent time and adjacent space. Real data based simulation shows the effectiveness of our proposed method. © 2019, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： Sensor nodes

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Adaptive Neural Admittance control for Collision Avoidance in Human-Robot Collaborative Tasks

Adaptive Neural Admittance Control for Collision Avoidance i...

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2019 IEEE/RSJ International Conference on Intelligent Robots and systems (IROS)

作者： Xinbo Yu Wei He Chengqian Xue Bin Li Long Cheng Chenguang Yang School of Automation and Electrical Engineering Institute of Artificial Intelligence University of Science and Technology Beijing Beijing China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Bristol Robotics Laboratory University of the West of England Bristol U.K

This paper proposed an adaptive neural admittance control strategy for collision avoidance in human-robot collaborative tasks. In order to ensure that the robot end-effector can avoid collisions with surroundings, robot should be operated compliantly by human within a constrained task space. An impedance model and a soft saturation function are employed to generate a differentiable reference trajectory. Then, adaptive neural network control with position constraint, based on integral barrier Lyapunov function (IBLF), is designed to achieve precise tracking while guaranteeing constrained satisfaction. Utilizing Lyapunov stability principles, we prove that semi-globally uniformly bounded stability is guaranteed for all states of the closed-loop system. At last, the effectiveness of the proposed algorithm is verified on a Baxter robot experimental platform. Collisions with surroundings can be avoided in human-robot collaborative tasks.

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Temporal-spatial cross-correlation analysis of non-stationary near-surface wind speed time series

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Journal of Central South University 2017年第3期24卷 692-698页

作者： ZENG Ming LI Jing-hai MENG Qing-hao ZHANG Xiao-nei Institute of Robotics and Autonomous Systems Tianjin Key Laboratory of Process Measurement and Control （School of Electrical Automation and Information Engineering Tianjin University） Tianjin 300072 China

Temporal-spatial cross-correlation analysis of non-stationary wind speed time series plays a crucial role in wind field reconstruction as well as in wind pattern ***,the near-surface wind speed time series recorded at different locations are studied using the detrended fluctuation analysis(DFA),and the corresponding scaling exponents are larger than *** indicates that all these wind speed time series have non-stationary ***,concerning this special feature( i.e.,non-stationarity)of wind signals,a cross-correlation analysis method,namely detrended cross-correlation analysis(DCCA) coefficient,is employed to evaluate the temporal-spatial cross-correlations between non-stationary time series of different anemometer ***,experiments on ten wind speed data synchronously collected by the ten anemometers with equidistant arrangement illustrate that the method of DCCA cross-correlation coefficient can accurately analyze full-scale temporal-spatial cross-correlation between non-stationary time series and also can easily identify the seasonal component,while three traditional cross-correlation techniques(i.e.,Pearson coefficient,cross-correlation function,and DCCA method) cannot give us these information directly.

关键词： temporal-spatial cross-correlation near-surface wind speed time series detrended cross-correlation analysis （DCCA） cross-correlation coefficient Pearson coefficient cross-correlation function

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Hand Tracking Accuracy Enhancement by Data Fusion Using Leap Motion and Myo Armband

Hand Tracking Accuracy Enhancement by Data Fusion Using Leap...

引用

International Conference on Unmanned systems and Artificial Intelligence

作者： Jingxiang Chen Chao Liu Rongxin Cui Chenguang Yang Key Laboratory of Autonomous Systems and Networked Control College of Automation Science and Engineering South China University of Technology Guangzhou China LIRMM CNRS-University of Montpellier France School of Marine Engineering Northwestern Polytechnical University Xi'an China Bristol Robotics Laboratory University of the West of England Bristol UK

ISBN: (数字)9781728158594

ISBN: (纸本)9781728158600

In this paper, by using the combination of Leap Motion and Myo armband, two methods for hand tracking and online hand gesture identification are proposed. With the proposed methods, We have improved the measurement accuracy of the palm direction and solved the problem of insufficient accuracy when the palm is at the limit of the measurement range. We use the Kalman filter algorithm and the neural network classification method to process the data measured by Leap Motion and Myo, so that the tracking of the operator's hand gesture is more accurate and robust even when the hand is at positions close to the measurement limit of one single sensor. The methods, which improve the hand tracking accuracy, can be used for robotic control, demonstration or teleoperation. The effectiveness of the proposed methods has been demonstrated through comparative experiments.

关键词： Leap Motion Myo sensor fusion hand tracking hand guesture identification Sensor fusion Hand arm band Data fusion tracking accuracy distance measurement improving precision accuracy of measurement Classification Methods Gestures data integration

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Development of a Tetris playing robot controlled by KNR 15

Development of a Tetris playing robot controlled by KNR

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15th IEEE International Conference on Mechatronics and Automation, ICMA 2018

作者： Wang, Ming Zhang, Yanlu Dong, Huifang Li, Xu Yu, Junzhi Department of Information and Electrical Engineering University of Shandong Jianzhu University Jinan250100 China Department of Intelligent Robotics State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China

ISBN: (纸本)9781538660720

Robot plays an increasingly important role in daily life. This paper presents a vision-based wheeled robot for playing Tetris. How to control the robot is elaborated at length in this paper. The robot adopted a KNR controller as its core controller. With a CCD sensor, it identified colored blocks, lines and the destination. All algorithms are programed with LabVIEW. The experiments and the contest validated the effectiveness of the proposed vision-based wheeled robot system. © 2018 IEEE.

关键词： controllers

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Study and modeling of a hull cleaning station with an arm manipulator

Study and modeling of a hull cleaning station with an arm ma...

引用

International Conference on Advanced systems and Electric Technologies (IC_ASET)

作者： Saber Hachicha Samir Nejim Chiheb Zaoui Aref Maalej Habib Dallagi Automatic Control & Marine Robotics Naval Academy Tunisia Laboratory of Electromechanical Systems of the University of Sfax Tunisia

The underwater hull cleaning is a center of interest of a big number of researchers from the fifties. Here we aim to facilitate the cleaning of the hull using a new robotic system with an arm manipulator. We developed the geometric and the dynamic modeling of the station components. In fact, the station has seven degrees of freedom four rotations and three translations. Besides, we used the SimMechanics software for the dynamic simulation of the station. In conclusion, our study shows that the underwater station with arm manipulator can be important for the hull cleaning ***.

关键词： Cleaning Solid modeling Marine vehicles End effectors Joints

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