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International Conference on Wireless Communications and Signal Processing (WCSP)

作者： Gengshan Wang Zhijia Yang Tierui Gong Meng Zheng State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China University of Chinese Academy of Sciences Beijing China Singapore University of Technology and Design Singapore

Dynamic subarrays (DSs) is an energy-efficient and cost-effective hybrid beamforming structure for millimeter wave (mmWave) multiple-input multiple-output (MIMO) communications. In this paper, we investigate the nonconvex hybrid beam-forming problem of maximizing the average spectral efficiency of the point-to-point wideband mmWave MIMO system with DSs, where the beam squints are also considered. To address the nonconvexity of this hybrid beamforming problem, we first exploit the singular value decomposition of each subcarrier channel and water-filling strategy to get the optimal fully-digital beamforming. We then propose to leverage the Kuhn-Munkres algorithm to get the hybrid beamforming from the obtained fully-digital solutions, aiming to guarantee that every radio-frequency chain is connected to at least one antenna. Besides, we analyze the computational complexity of the proposed design. Numerical results demonstrate the superiority of this work over the state of the art.

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A heterogeneous master-slave teleoperation method for 7-DOF manipulator

A heterogeneous master-slave teleoperation method for 7-DOF ...

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2021 China Automation Congress, CAC 2021

作者： Su, Rong Xu, Ke Zhao, Liang Yu, Peng School of Information and Control Engineering Shenyang Jianzhu University Shenyang China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China University of Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781665426473

Teleoperation is widely used because of its ability to extend human behavior and perception to slave robots. In this paper, we use a wearable exoskeleton as the master device for human-robot interaction, which can obtain the movement posture of the operator naturally and intuitively. The slave device uses a 7-DOF redundant manipulator similar to the human arm structure, which improves flexibility without being over redundant. In addition, an inverse kinematics method is proposed to meet the requirements of anthropomorphic remote operation of master-slave heterogeneity. Simulation experiments are carried out in combination with MATLAB and ROS RVIZ environment to prove the performance of the heterogeneous teleoperation control method. © 2021 IEEE

关键词： Inverse kinematics

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Development of Method of Generating a Reference Movement Speed of a Group of UAVs

Development of Method of Generating a Reference Movement Spe...

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Ocean Studies (ICOS), International Conference on

作者： Anton Gubankov Igor Gornostaev Robotics Laboratory Laboratory of intelligent information systems for marine robots Laboratory of Marine Unmanned Aviation and Marine Aviation Systems Institute of Automation and Control Processes FEB RAS M.D. Ageev Institute of Marine Technology Problems FEB RAS Admiral G.I. Nevelskoy Maritime State University Vladivostok Russia Robotics Laboratory Laboratory of Robotic Systems Laboratory of Marine Unmanned Aviation and Marine Aviation Systems Institute of Automation and Control Processes FEB RAS M.D. Ageev Institute of Marine Technology Problems FEB RAS Admiral G.I. Nevelskoy Maritime State University Vladivostok Russia

ISBN: (数字)9798331532307

ISBN: (纸本)9798331532314

The article presents the results of the development of a method for the automatic formation of reference speeds for autonomous unmanned aerial vehicles of multirotor type, performing specified missions (such as monitoring of the sea and coastal territory in order to track populations of rare and endangered species, as well as evaluating the potential volumes of biological resources) singly or as part of a group (in formation). At the same time, the trajectories of these aircraft are set by smooth spatial curves - parametric splines of the third order, which makes it easy to adjust the specified trajectories during the mission. In order to maintain a high speed of movement of vehicles along trajectories with high accuracy of movement and saving formation, it is proposed to adjust the specified speed directly during the mission in such a way that the thrusters can ensure their required movements, taking into account the restrictions on the thrust vectors. At the same time, a simplified model of the dynamics of a quadcopter was used to calculate the values of reference speeds, taking into account the influence of wind force, environmental resistance, gravity and the total thrust vector of the propellers. The systems synthesized on the basis of this method can be implemented even on low-power onboard computing devices of unmanned aerial vehicles.

关键词： Accuracy Sea measurements Autonomous aerial vehicles Vectors Real-time systems Trajectory Aircraft Vehicle dynamics Splines (mathematics) Standards

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Unsupervised Learning of 3D Scene Flow from Monocular Camera

arXiv

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arXiv 2022年

作者： Wang, Guangming Tian, Xiaoyu Ding, Ruiqi Wang, Hesheng Department of Automation Institute of Medical Robotics Key Laboratory of System Control and Information Processing of Ministry of Education Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai 200240 China

Scene flow represents the motion of points in the 3D space, which is the counterpart of the optical flow that represents the motion of pixels in the 2D image. However, it is difficult to obtain the ground truth of scene flow in the real scenes, and recent studies are based on synthetic data for training. Therefore, how to train a scene flow network with unsupervised methods based on real-world data shows crucial significance. A novel unsupervised learning method for scene flow is proposed in this paper, which utilizes the images of two consecutive frames taken by monocular camera without the ground truth of scene flow for training. Our method realizes the goal that training scene flow network with real-world data, which bridges the gap between training data and test data and broadens the scope of available data for training. Unsupervised learning of scene flow in this paper mainly consists of two parts: (i) depth estimation and camera pose estimation, and (ii) scene flow estimation based on four different loss functions. Depth estimation and camera pose estimation obtain the depth maps and camera pose between two consecutive frames, which provide further information for the next scene flow estimation. After that, we used depth consistency loss, dynamic-static consistency loss, Chamfer loss, and Laplacian regularization loss to carry out unsupervised training of the scene flow network. To our knowledge, this is the first paper that realizes the unsupervised learning of 3D scene flow from monocular camera. The experiment results on KITTI show that our method for unsupervised learning of scene flow meets great performance compared to traditional methods Iterative Closest Point (ICP) and Fast Global Registration (FGR). The source code is available at: https://***/IRMVLab/3DUnMonoFlow. Copyright © 2022, The Authors. All rights reserved.

关键词： Unsupervised learning

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Frame analysis based real time related indicators measurement of industrial ethernet Powerlink

Frame analysis based real time related indicators measuremen...

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Science and Technology Innovation (IAECST), International Academic Exchange Conference on

作者： Jian Wang Chuang Xie Ce Dong Key Laboratory of Networked Control System Shenyang Institute of Automation Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences ShenYang China

The protocol Powerlink which is one of real-time Ethernet protocols included in the Standard IEC FDIS61784-2, has been widely used for the communication of both IO devices in industrial fields and drives for motor control applications to provide deterministic data transmission. When the Powerlink network is running in the industrial field environment, the online measurement of time related indicators is an appropriate method to evaluate the performance of the network in real time and detect communication faults between devices. In this paper, several time related indicators are proposed and analyzed to estimate the real time performance of the network when all devices get into the operate state. Further more, an efficient method to measure the proposed indicators based on frame analysis is presented and implemented on a PC-based monitor station that stores all the frames which transfer in the network and contain timestamp added by an FPGA-based probe. The measurement method is tested on a real network consisting of one master node and two slave nodes, and some experimental results are presented.

关键词： Performance evaluation Technological innovation Protocols Stability criteria Ethernet Real-time systems Time measurement

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Short-term load forecasting of long-short term memory neural network based on genetic algorithm 4

Short-term load forecasting of long-short term memory neural...

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4th IEEE Conference on Energy Internet and Energy System Integration, EI2 2020

作者： Li, Wanting Zang, Chuanzhi Liu, Ding Zeng, Peng Shenyang Institute of Automation Chinese Academy of Sciences Key Laboratory of Networked Control Systems State Key Laboratory of Robotics Institutes for Robotics and Intelligent Manufacturing Beijing China

ISBN: (纸本)9781728196060

Accurate load forecasting is conducive to the reasonable arrangement of power grid dispatching plans. Traditional load forecasting methods cannot handle the time series and nonlinear characteristics of load well. Long-short term memory (LSTM) neural networks can record long-term and short-term information, which can effectively solve this kind of problem. But the parameters of LSTM network are difficult to determine. For this reason, this paper proposes a long-short term neural network based on genetic algorithm. The learning rate and iteration number of the LSTM network are used as chromosomes, and the genes are continuously selected, crossed, and mutated to obtain more good genes. Comparing this method with the standard LSTM network, the simulation results show that the LSTM network using genetic algorithm for parameter optimization improves the prediction accuracy of the standard LSTM network by 63%. © 2020 IEEE.

关键词： Genetic algorithms

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A non-interactive verifiable computation model of perceptual layer data based on CP-ABE 2

A non-interactive verifiable computation model of perceptual...

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2nd International Conference on Consumer Electronics and Computer Engineering, ICCECE 2022

作者： Zhao, Jianming Miao, Weiwei Zeng, Zeng Chinese Academy of Sciences Key Laboratory of Networked Control Systems Shenyang China Chinese Academy of Sciences Shenyang Institute of Automation Shenyang China Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Shenyang China State Grid Jiangsu Electric Power Co. Ltd. Information Telecommunication Branch Nanjing China

ISBN: (纸本)9781665408868

The computing of smart devices at the perception layer of the power Internet of Things is often insufficient, and complex computing can be outsourced to server resources such as the cloud computing, but the allocation process is not safe and controllable. Under special constraints of the power Internet of Things such as multi-users and heterogeneous terminals, we propose a CP-ABE-based non-interactive verifiable computation model of perceptual layer data. This model is based on CP-ABE, NPOT, FHE and other relevant safety and verifiable theories, and designs a new multi-user non-interactive secure verifiable computing scheme to ensure that only users with the decryption key can participate in the execution of NPOT Scheme. In terms of the calculation process design of the model, we gave a detailed description of the system model, security model, plan. Based on the definition given, the correctness and safety of the non-interactive safety verifiable model design in the power Internet of Things environment are proved, and the interaction cost of the model is analyzed. Finally, it proves that the CP-ABE-based non-interactive verifiable computation model for the perceptual layer proposed in this paper has greatly improved security, applicability, and verifiability, and is able to meet the security outsourcing of computing in the power Internet of Things environment. © 2022 IEEE.

关键词： Internet of things

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Trajectory Tracking Error Optimization based on Iterative Learning 4

Trajectory Tracking Error Optimization based on Iterative Le...

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4th IEEE International Conference on Power, intelligent Computing and Systems, ICPICS 2022

作者： Huang, Haoran Zhang, Tao Jia, Danping Zhang, Hualiang Yan, Hongyu Pei, Quanshen Ding, Fan Shenyang University of Technology School of Information Science and Engineering Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang Institute of Automation Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China School of Artificial Intelligence Shenyang University of Technology Shenyang China

ISBN: (数字)9781665467735

ISBN: (纸本)9781665467735

The X-Y precision plane motion platform is widely used in various precision motion control fields. In this paper, to improve the tracking accuracy of the X-Y precision plane motion table, a high-level iterative learning control with forgetting factor is proposed, and it is combined with a kind of PD-type iterative learning control with low-pass filter, and the method is applied to the Simulink model of the linear motor of the X-Y precision plane platform, thereby improving the trajectory accuracy of the X-Y precision plane motion platform. The traditional ILC has the disadvantage that the more number of iterations, the more divergent tracking error is. The new ILC proposed in this paper can not only effectively reduce the noise, reduce the tracking error, but also eliminate the problem of error divergence caused by too many iterations. At last, the experimental results of high-order PD iterative learning with forgetting factor and low-pass filter, PD iterative learning with low-pass filter, ordinary PD iterative learning are compared. The results show that the high-order PD iterative learning with forgetting factor and low-pass filter has better tracking effect than the first-order iterative learning and other several algorithms. It can make the movement trajectory of the X-Y precision plane motion platform more stable and improve the accuracy. © 2022 IEEE.

关键词： Low pass filters

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Optimization method of Data interaction in power IoT based on particle swarm algorithm 2

Optimization method of Data interaction in power IoT based o...

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2nd International Conference on Consumer Electronics and Computer Engineering, ICCECE 2022

作者： Wang, Tianyu Miao, Weiwei Zeng, Zeng Chinese Academy of Sciences Key Laboratory of Networked Control Systems Shenyang China Chinese Academy of Sciences Shenyang Institute of Automation Shenyang China Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Shenyang China State Grid Jiangsu Electric Power Co. Ltd. Information Telecommunication Branch Nanjing China

ISBN: (纸本)9781665408868

The ubiquitous power Internet of things (IoT) constructs an intelligent service system with comprehensive perception, efficient response and flexible processing around all departments of the power system and with the support of communication technologies such as mobile Internet and artificial intelligence. With the rapid development of smart IoT perceptual devices and edge computing, it has become possible for perceptual devices and edge IoT agents to cooperate in processing tasks. The task completion time can be greatly reduced through the cooperative processing among multiple entities in the IoT. However, as the scale of the Internet of things and number of to-be-processed tasks expanding year by year, the simple task data interaction between devices can not meet the needs of the completion time. Therefore, it is an urgent problem to optimize data transmission and data interaction in the process of collaborative task processing among IoT devices. Motivated by this point, we propose an optimization method of data interaction in power IoT based on particle swarm algorithm. Evaluation on example IoT networks shows the effectiveness of our method to reduce overall task completion time. © 2022 IEEE.

关键词： Internet of things

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Service Encapsulation Method Based on Industrial Internet

Service Encapsulation Method Based on Industrial Internet

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作者： Li, Kai Pan, Hao Tong, Xing Li, Dong Wang, Ting Shenyang University of Chemical Technology Liaoning Shenyang110142 China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Liaoning Shenyang110016 China Shenyang Institute of Automation Chinese Academy of Sciences Liaoning Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Liaoning Shenyang110016 China

Based on the analysis of software and hardware integration and highly heterogeneous infrastructure in the traditional industrial field, this paper puts forward the concept of service packaging engine, puts forward a unified service packaging model for Industry by using the Internet thinking design mode, and can complete the control of complex industrial field equipment by editing only simple logic in the programming interface. This article focuses on basic service encapsulation. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Computer programming

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