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检索条件"任意字段=5th International Conference on Robotics and Automation Systems, Robotics 2010"

共 1360 条记录，以下是521-530 订阅

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Attitude Stabilization of Spacecraft Perturbed by Tether-Captured Debris 8

Attitude Stabilization of Spacecraft Perturbed by Tether-Cap...

引用

8th IEEE Annual international conference on Cyber Technology in automation, Control, and Intelligent systems (IEEE-CYBER)

作者： Zhai Guang Bi Xingzi Zheng Heming Beijing Inst Technol Sch Aerosp Engn POB 255 Zhongguancun South St Beijing Peoples R China

ISBN: (纸本)9781538670576

In this paper, we studied the attitude dynamics and control problem of a tethered space robot system, which are perturbed by a librational tether. First, the dynamics of the platform is developed with considering the librational tether. Secondly, a nonlinear disturbance observer is proposed based on attitude rate observations. Finally, a robust attitude controller is developed by using the disturbance observer an a PD controller, and the advantages from the proposed controller is demonstrated by numerical simulations.

关键词： aerospace robotics attitude control nonlinear control systems observers PD control robust control space vehicles stability aerospace robotics Proportional derivative control Space vehicles Nonlinear control systems attitude control Robust control disturbance observer attitude dynamics Observers attitude stabilisation attitude controllers

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Towards Edge Computing Based Distributed Data Analytics Framework in Smart Grids 5th

Towards Edge Computing Based Distributed Data Analytics Fram...

引用

5th international conference on Artificial Intelligence and Security, ICAIS 2019

作者： Song, Chunhe Li, Tong Huang, Xu Wang, Zhongfeng Zeng, Peng Chinese Academy of Sciences Shenyang Institute of automation Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110016 China Liaoning Electric Power Research Institute State Grid Liaoning Electric Power Co. Ltd. Shenyang110000 China Shenyang Power Supply Company State Grid Liaoning Electric Power Co. Ltd. Shenyang110000 China

ISBN: (纸本)9783030242732

Edge computing, as an emerging paradigm empower the network edge devices with intelligence, has become a prominent and promising future for Internet of things. Meanwhile, machine learning method, especially deep learning method has experience tremendous success recently in many application scenario. Recently, deep learning method applied in IoT scenario is also explored in many literatures. However, how to combine edge computing and deep learning method to advance the data analytics in smart grids has not been fully studied. To this end, in this paper, we propose ECNN (Edge-deployed Convolution Neural Network) in edge computing assisted smart grids to greatly enhance the ability in data aggregation and analytics. We also discuss how to train such network in edge computing distributively. Experiments shows the advantage of our paradigm. © 2019, Springer Nature Switzerland AG.

关键词： Edge computing

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End-to-end Learning for Autonomous Crop Row-following 6th

End-to-end Learning for Autonomous Crop Row-following

引用

6th international-Federation-of-Automatic-Control (IFAC) conference on Sensing, Control and automation Technologies for Agriculture (AGRICONTROL)

作者： Bakken, Marianne Moore, Richard J. D. From, Pal SINTEF Digital Oslo Norway Norwegian Univ Life Sci NMBU As Norway

For robotic technology to be adopted within the agricultural domain, there is a need for low-cost systems that can be flexibly deployed across a wide variety of crop types, environmental conditions, and planting methods, without extensive re-engineering. Here we present an approach for predicting steering angles for an autonomous, crop row-following, agri-robot using only RGB image input. Our approach employs a deep convolutional neural network (DCNN) and an end-to-end learning strategy. We pre-train our network using existing open datasets containing natural features and show that this approach can help to preserve performance across diverse agricultural settings. We also present preliminary results from open-loop field tests that demonstrate the feasibility and some of the limitations of this approach for agri-robot guidance. (C) 2019, IFAC (international Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Robot vision Robot navigation Machine learning Agricultural robotics Mobile robots

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Power Consumption and Coverage Test of NB-IoT in the Substation Edge Computing Environment 1

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5th international conference on Artificial Intelligence and Security, ICAIS 2019

作者： Song, Chunhe Li, Huan Wang, Zhongfeng Ren, Shuai Zeng, Peng Chinese Academy of Sciences Shenyang Institute of Automation Shenyang110016 China Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Shenyang110016 China Liaoning Electric Power Research Institute State Grid Liaoning Electric Power Co. Ltd. Shenyang110000 China

ISBN: (数字)9783030242657

ISBN: (纸本)9783030242640

With the continuous development of smart grids, the application of Internet of things technology in the substation edge computing environment is becoming more and more widespread. Traditional communication technologies, such as ZigBee and 4G, have limited transmission distances with low reliability, or high power consumption with inconvenient deployment. Narrowband Internet of things (NB-IoT) is a new cellular technology introduced in 3GPP with wide coverage, large capacity, low power consumption and low cost. It provides a new kind of IoT communication technique in substation, which has complex electromagnetic interference that can cause interference to wireless transmission. In this paper, the power consumption and coverage performance of NB-IoT devices in substation environment are tested by our testbed-based experimental study. We leverage results from our experiments in providing an analysis on the power consumption and the impact of coverage when there are complex electromagnetic interferences. © 2019, Springer Nature Switzerland AG.

关键词： Internet of things

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A Novel Power System Anomaly Data Identification Method Based on Neural Network and Affine Propagation 1

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5th international conference on Artificial Intelligence and Security, ICAIS 2019

作者： Shen, Li Shen, Yang Song, Chunhe Li, Zhao Ran, Ran Zeng, Peng State Grid Liaoning Electric Power Co. Ltd. Shenyang110000 China Shenyang Institute of automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110016 China

ISBN: (数字)9783030242657

ISBN: (纸本)9783030242640

Identification of anomaly data is very important for power system state estimation. In this paper, a method of power system anomaly data identification based on neural network and affine propagation is proposed. In this first step, a 3-layer neural network is trained as a predictor using normal data. In the second step, data to be detected is preprocessed using the trained neural network, and predicted residuals are obtained. In the third step, these predicted residuals are clustered using the affine propagation clustering algorithm, and in the final step, anomaly data is identified based on the clustering results. As the neural network training process is easy to fall into local minimum, which reduces the prediction accuracy of the neural network, in this paper a novel chaotic particle swarm optimization algorithm is proposed to train the neural network. From the experimental results it can be seen that, compared with previous anomaly data identification method using the BP neural network and the gap statistic algorithm or the K-mean clustering algorithm, the proposed method can effectively improve the accuracy of anomaly data identification. © 2019, Springer Nature Switzerland AG.

关键词： Neural networks

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Task-based Programming and Sequence Planning for Human-Robot Collaborative Assembly 9

Task-based Programming and Sequence Planning for Human-Robot...

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9th IFAC/IFIP/IFORS/IISE/INFORMS conference on Manufacturing Modelling, Management and Control (IFAC MIM)

作者： Aliev, Khurshid Antonelli, Dario Bruno, Giulia Politecn Torino Corso Duca Abruzzi 24 I-10129 Turin Italy

the paper proposes a task-based programming method to support assembly processes in a human-robot collaborative workcell. the method for assembly sequence generation is implemented as a robot program homebuilt by composing pre-programmed elementary working steps. Developed system can support human operator as an interactive tool for collaboration with robot. Robot program and developed software are used to interface the robot with the human during the execution of the assembly tasks starting from single mechanical parts. the proposed Human Robot Interaction System (HRIS) performs an assembly job with the contemporary collaborative work of robots and humans that share tasks in the same workspace. the system is tested on a case study made on purpose and constituted by several different flanges mounted on a support in a variety of configurations. thus, the method is general and can be easily adapted to a multiplicity of assembly tasks. (C) 2019, IFAC (international Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

关键词： robotics in manufacturing Human-automation Integration Production Control Control systems

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Control systems: theory and Applications 1

引用

丛书名： River Publishers series in automation, control and robotics

2018年

作者： international conference on Automatic Control

ISBN: (数字)9788770220255

ISBN: (纸本)9788770220248

In recent years, a considerable amount of effort has been devoted, both in industry and academia, towards the development of advanced methods of control theory with focus on its practical implementation in various fields of human activity such as space control, robotics, control applications in marine systems, control processes in agriculture and food production. Control systems: theory and Applications consists of selected best papers which were presented at XXIV international conference on automatic control “Automatics 2017” (September 13–15, 2017, Kyiv, Ukraine) organized by Ukrainian Association on Automatic Control (National member organization of IFAC – international Federation on Automatic Control) and National University of Life and Environmental Sciences of Ukraine. More than 120 presentations where discussed at the conference, with participation of the scientists from the numerous countries. the book is divided into two main parts, a first on theory of Automatic Control (5 chapters) and the second on Control systems Applications (8 chapters). the selected chapters provide an overview of challenges in the area of control systems design, modeling, engineering and implementation and the approaches and techniques that relevant research groups within this area are employing to try to resolve these. this book on advanced methods of control theory and successful cases in the practical implementation is ideal for personnel in modern technological processes automation and SCADA systems, robotics, space and marine industries as well as academic staff and master/research students in computerized control systems, automatized and computer-integrated systems, electrical and mechanical engineering.

关键词： Industrial management-United States

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Robust and High-Precision End-to-End Control Policy for Multi-stage Manipulation Task with Behavioral Cloning 4th

Robust and High-Precision End-to-End Control Policy for Mult...

引用

4th international conference on Cognitive systems and Information Processing, ICCSIP 2018

作者： Ge, Wei Shang, Weiwei Song, Fangjing Sui, Hongjian Cong, Shuang Department of Automation University of Science and Technology of China Hefei China

ISBN: (纸本)9789811379826

In this paper, we propose a multi-stage task learning method that trains an end-to-end policy to control a 6-DoF robot arm to accomplish pick-and-place operation with high precision. the policy is mainly composed of CNNs and LSTMs, directly mapping raw images and joint angles to velocities command. In order to acquire a robust and high-precision policy, several techniques are introduced to boost performance. Augmentation trajectories are designed to alleviate compounding error problem, and dataset resampling is used to solve imbalanced data issue. Moreover, Huber loss for auxiliary outputs is illustrated to be very effective in multi-objective optimization problems, especially in robot learning field where sample complexity needs to be reduced desirably. To verify the effectiveness of our method, experiments are carried out in Gazebo simulator with UR5 arm and Kinect v1 camera. Our visuomotor policy can achieve a success rate of $$87\%$$ on the pick-and-place task. the results of our experiments demonstrate that, with the skills we mention, behavioral cloning can effectively help us to learn good visuomotor policies for long-horizon tasks. © 2019, Springer Nature Singapore Pte Ltd.

关键词： Cloning

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An Improved Method for the Error Modeling of a 5-DoF Parallel Machining Robot Based on Measurement by a Laser Tracker

An Improved Method for the Error Modeling of a 5-DoF Paralle...

引用

IEEE international conference on Cyber Technology in automation, Control, and Intelligent systems

作者： Xuan Luo Fugui Xie Xin-Jun Liu Zenghui Xie Zaihua Yang State Key Laboratory of Tribology & Tsinghua University (DME) Siemens Joint Research Center for Advanced Robotics and Beijing Key Lab of Precision Tsinghua University Beijing China Beijing Institute of Spacecraft Environment Engineering Beijing China

ISBN: (数字)9781728107707

ISBN: (纸本)9781728107714

Kinematic calibration of 5-DoF parallel robots is very challenging, due to the difficulty in accomplishing the efficient and precise measurement of the end-effector's pose errors, and the situation that the terms of the error mapping Jacobian matrix (EMJM) in various units will restrict the identification accuracy. this paper proposes an improved error modeling method based on measurement by a laser tracker to deal with these problems for a 5-DoF parallel machining robot, DiaRoM-II. Two steps of modeling modification are developed as: (1) reselecting the robot's geometric errors in a uniform unit; (2) substituting the pose errors of the end-effector with the position errors of two points along the axis of the spindle. Accordingly, the dimensionless EMJM is established. On this basis, the identification simulation experiments are conducted, and the results verify that the improved error modeling method is effective in accurately identifying the geometric errors of DiaRoM-II.

关键词： Frequency modulation conferences automation Control systems Intelligent systems 5G mobile communication

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A Novel Prediction Algorithm for the Cross Temperature Estimation of Blast Furnace

A Novel Prediction Algorithm for the Cross Temperature Estim...

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international conference on Electrical Engineering, Control and robotics

作者： Yan Jin Sen Zhang YiXin Yin School of Automation and Electrical Engineering University of Science and Technology Beijing

ISBN: (纸本)9781510887374

In order to predict the distribution of gas flow, we need to get the temperature of each point in blast furnace throat in advance. In this paper, firstly, two intelligent modeling methods are used to establish a multiple-input multiple-output prediction model, one is extreme learning machine(ELM) algorithm and the other is online sequential extreme learning machine(OS-ELM) algorithm. And the model is a single-step prediction model of temperature in blast furnace, single-step prediction means the prediction of temperature in the next moment. We use autocorrelation analysis to determine input vector and output vector of the model. the result of autocorrelation analysis indicates that the method of temperature sequence prediction has a higher prediction accuracy and better prediction stability than the method of single point prediction. Next, based on real industrial data, we make a comparison between the multipleinput multiple-output model and least squares support vector machines(LS-SVM) model used in common. the experiment results show that OS-ELM model has a better forecast effect than the ELM model and LS-SVM model.

关键词： ELM A Novel Prediction Algorithm for the Cross Temperature Estimation of Blast Furnace

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