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International Conference on Military Communications and Information systems (ICMCIS)

作者： J. DeMarchi R. Rijken J. Melrose B. Madahar G. Fumera F. Roli E. Ledda M. Aktaş F. Kurth P. Baggenstoss B. Pelzer L. Kanestad Collaborative Engineering Systems & Aerospace Systems Information Supremacy Royal Netherlands Aerospace Centre NLR Amsterdam NLD Cyber & Information Systems Division Defence Science and Technology Laboratory Portondown GBR Department of Electrical and Electronic Engineering University of Cagliari Cagliari ITA Department of Informatics Bioengineering Robotics and Systems Engineering University of Genoa Genoa ITA Department of Computer Control and Management Engineering Sapienza University of Rome Rome ITA Defence Systems Technologies Division ASELSAN Ankara TUR Fraunhofer Institute for Communication Information Processing and Ergonomics Bonn DEU Swedish Defence Research Agency Cyber Defence and C2 Technology Division Stockholm SWE

In this paper we explore some of the potential applications of robustness criteria for machine learning (ML) systems by way of tangible “demonstrator” scenarios. In each demonstrator, ML robustness metrics are applied to real-world scenarios with military relevance, indicating how they might be used to help detect and handle possible adversarial attacks on ML systems. We conclude by sketching promising future avenues of research in order to: (1) help establish useful verification methodologies to facilitate ML robustness compliance assessment; (2) support development of ML accountability mechanisms; and (3) reliably detect, repel, and mitigate adversarial attack.

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Edge computing-based defect identification model of power IoT edge side devices

Edge computing-based defect identification model of power Io...

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2020 IEEE International Conference on Information Technology, Big Data and Artificial Intelligence, ICIBA 2020

作者： Li, Dawei Jia, Gengtao Song, Chunhe Yu, Shimao Start Grid Shanghai Information Telecommunication Company Shanghai200122 China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang11016 China

ISBN: (纸本)9781728152240

There are various types of devices on the terminal side of the power Internet of Things, and the data collected through various sensors shows an exponential growth. The current in-depth application of edge computing technology can not only ease the pressure of network transmission, but also improve the timeliness of fault diagnosis. Edge computing technology is A new way to solve the fault diagnosis of equipment on the edge of the power grid. From the perspective of edge fault diagnosis, this paper expounds the fault diagnosis model of power IoT edge devices based on edge computing, and combines the isolated forest algorithm to design smart sensor data-based power IoT edge device fault diagnosis algorithms. Finally, the validity of the proposed framework model is verified by public sample data. © 2020 IEEE.

关键词： Failure analysis

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Distributed computing framework of intelligent sensor network for electric power internet of things 9

Distributed computing framework of intelligent sensor networ...

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9th IEEE Joint International Information Technology and Artificial Intelligence Conference, ITAIC 2020

作者： Li, Dawei Yu, Ruimo Song, Chunhe Li, Shu Jia, Gengtao Zhou, Xiaoli Start Grid Shanghai Information Telecommunication Company Shanghai200122 China Shenyang Institute of Automation Chinese Academy of Sciences State Key Laboratory of Robotics Shenyang110016 China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China

The power IoT terminal environment is complex, and current smart sensor sensors have problems such as poor networking capabilities and large processing delays, and few specific edge-side automatic networking capabilities. This paper analyzes and elaborates the distributed intelligent sensor computing framework from the perspective of edge intelligent networking, designs a computing model for intelligent sensors of power Internet of Things terminals, and gives the edge-based deployment of convolutional neural network architecture, data aggregation, model training, and intelligent reasoning. Finally, the validity of the proposed framework model is verified by public sample data. © 2020 IEEE.

关键词： Internet of things

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Information modeling and verification method for edge computing of power internet of things 9

Information modeling and verification method for edge comput...

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9th IEEE Joint International Information Technology and Artificial Intelligence Conference, ITAIC 2020

作者： Li, Dawei Chen, Xiaolu Song, Chunhe Yu, Shimao Start Grid Shanghai Information Telecommunication Company Shanghai200122 China Shenyang Institute of Automation Chinese Academy of Sciences State Key Laboratory of Robotics Shenyang110016 China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China

There are various types of power Internet of Things terminals, and a unified edge-side information fusion model is the basis of data unification. This article describes the unified modeling method of power Internet of Things terminal information, and describes the construction method of the Internet of Things terminal information model from three aspects: attribute, message and service. Combined with the characteristics of the electric power Internet of Things information model, a model verification method is given. Finally, through the terminal data on the edge side of the power Internet of Things, the feasibility and effectiveness of the model verification method are verified. © 2020 IEEE.

关键词： Internet of things

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Fully Robotized 3D Ultrasound Image Acquisition for Artery

Fully Robotized 3D Ultrasound Image Acquisition for Artery

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IEEE International Conference on robotics and Automation (ICRA)

作者： Mingcong Chen Yuanrui Huang Jian Chen Tongxi Zhou Jiuan Chen Hongbin Liu State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Centre for Artificial Intelligence and Robotics Hong Kong Institute of Science and Innovation Chinese Academy of Sciences Hong Kong School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China School of Biomedical Engineering and Imaging Sciences King's College London London UK

Current imaging of the artery relies primarily on computed tomography angiography (CTA), which requires contrast injections and exposure to radiation. In this paper, we present a method for fully autonomous artery 3D image acquisition using a linear ultrasound (US) probe and a 6 DoFs robot arm with a 3D camera. Robotic vessel acquisition can minimize tissue deformation and permit the reproduction of scans. Additionally, the robotic-based acquisition can provide more precise vessel position data that can be utilized for 3D reconstruction as a preoperative image. The first scanning point is determined by the 3D camera using a neural network for leg area estimation. A visual servo algorithm adjusts the in-plane motions using a cross-sectional vessel segmentation produced by a neural network with a UNet structure, while a US confidence map regulates the in-plane rotation. The robot is equipped with impedance control to maintain a constant and safe scan. Experiments on a leg phantom and a volunteer indicate that the robot can follow the vessel and modify its position to provide a sharper US image. The average error of phantom scanning in y-axis and z-axis are 0.2536mm and 0.2928mm, respectively, while the root means square error (RMSE) of contact force in the volunteer experiment is 0.2664N. In addition, a 3D vessel reconstruction demonstrates the possibility of robotic US acquisition as a preoperative image.

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Position control of X-Y Precision Motion Stage Based on Iterative Learning and Model Prediction

Position Control of X-Y Precision Motion Stage Based on Iter...

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Chinese control and Decision Conference, CCDC

作者： Guopeng Zhang Tao Zhang Qingxin Li Li Chen Hualiang Zhang Jingzhe Fang Yiqiang Zhang School of Artificial Intelligence Shenyang University of Technology Shenyang Institute of Automation Chinese Academy of Sciences 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 School of Electrical Engineering Shenyang University of Technology Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China

ISBN: (数字)9798350387780

ISBN: (纸本)9798350387797

The X-Y precision planar motion stage is a highly advanced motion control device that has been widely utilized in various precision motion control fields. This platform achieves precise positioning and control of objects through precise motion along the X and Y axes, providing an outstanding solution for scientific research, industrial production, and other applications. The X-Y platform consists of two permanent magnet synchronous linear motors. In the three-loop control of the motor, when the current loop uses a PID controller, there is a problem in tuning the parameters. This paper replaces the original PID controller in the current loop with a model predictive controller. Simultaneously, addressing the issue of improving the tracking accuracy of the X-Y precision planar motion stage, a forgetting high-order variable gain PD-type iterative learning control is proposed. Subsequently, both of these control methods are applied to the Simulink model of the X-Y precision motion stage motor. This not only solves the complex problem of tuning the motor current loop parameters but also improves the tracking accuracy of the X-Y precision motion stage. The results indicate that when using both model predictive controllers and forgetting high-order variable gain PD-type iterative learning controllers for motor control, not only can the tuning of current loop parameters be omitted, but also tracking errors can be effectively reduced, and the system convergence speed can be accelerated.

关键词： Tracking loops Trajectory tracking Predictive models Motors Mathematical models Motion control Tuning

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Generating Datasets for Real-Time Scheduling on 5g New Radio

SSRN

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SSRN 2022年

作者： Jin, Xi Chai, Haoxuan Xia, Changqing Xu, Chi Zeng, Peng Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang110016 China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China University of Chinese Academy of Sciences Beijing100049 China

5G is an advanced solution for industrial wireless motion control. However, since the scheduling model of 5G new radio (NR) is more complicated than those of other wireless networks, existing real-time scheduling algorithms cannot be used to improve the 5G performance. This results in NR resources not being fully available for industrial systems. Supervised learning has been widely used to solve complicated problems, and its advantages have been demonstrated in multiprocessor scheduling. One of the main reasons why supervised learning has not been used for 5G NR scheduling is the lack of training datasets. Therefore, in this paper, we propose two methods based on optimization modulo theories (OMT) and satisfiability modulo theories (SMT) to generate training datasets for 5G NR scheduling. Our OMT-based method contains fewer variables than existing work so that the Z3 solver can find optimal solutions quickly. To further reduce the solution time, we transform the OMT-based method into an SMT-based method and tighten the search space of SMT based on three theorems and an algorithm. Finally, we conduct extensive evaluations. The evaluation results indicate that our SMT-based method reduces the solution time by 74.7% compared to existing ones. © 2022, The Authors. All rights reserved.

关键词： Scheduling algorithms

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Development of a Vision Aided Automated Ball Retrieving Robot for Tennis Training Sessions 14

Development of a Vision Aided Automated Ball Retrieving Robo...

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14th IEEE International Conference on Industrial and Information systems, ICIIS 2019

作者： Perera, Dulanjana M. Menaka, G.M.D. Surasinghe, W.V.K.M. Kanishka Madusanka, D.G. Lalitharathne, Thilina Dulantha Robotics and Control Systems Laboratory University of Moratuwa Department of Mechanical Engineering 10400 Sri Lanka

ISBN: (纸本)9781728137063

A single training session of tennis requires 30-40 balls and these scattered balls have to be collected at the end of each session which costs time and induces unnecessary physical stress on players. This paper proposes a method to retrieve the balls which are scattered in the Tennis court back to the user. The proposed method comprises image processing techniques for object localization and the adaptation of Dijkstra's algorithm for optimum path planning for efficient navigation. Both localization and the path planning algorithms are developed on a Python platform and robot's differential drive system is controlled by a microcontroller. Communication between robot and the computer is established through Wi-Fi. Novel development of this research is the implementation of the global view method for a vast range of image acquisition and verifying its suitability in Tennis field. In order to collect balls efficiently, an adaption of an existing mechanism is proposed. Results show that the mechanism is 80% efficient in collecting balls and 100% efficient in object identification for a given environmental condition. © 2019 IEEE.

关键词： Mobile robots

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Simultaneous Precision Assembly of Multiple Objects through Coordinated Micro-robot Manipulation

Simultaneous Precision Assembly of Multiple Objects through ...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Song Liu Yuyu Jia You-Fu Li Yao Guo Haojian Lu ShanghaiTech Automation and Robotics Center School of Information Science and Technology ShanghaiTech University Shanghai China City University of Hong Kong Kowloon Hong Kong Institute of Medical Robotics Shanghai Jiaotong University Shanghai China State Key Laboratory of Industrial Control and Technology and Institute of Cyber-Systems and Control Zhejiang University Hangzhou China

Simultaneous assembly of multiple objects is a key technology to form solid connections among objects to get compact structures in precision assembly and micro-assembly. Dramatically different from traditional assembly of two objects, the interaction among multiple objects is more complicated on analysis and control. During simultaneous assembly of multiple objects, there are multiple mutually effected contact surfaces, and multiple force sensors are needed to perceive the interaction status. In this paper, a coordinated micro-robot manipulation strategy is proposed for simultaneous assembly problem, which is based on microscopic vision and force information. Taking simultaneous assembly of three objects as an instance, the proposed method is well articulated, including calibration of assembly system, force analysis for each contacting surface, and insertion control strategy for assembly process. The proposed method is applicable also to case with more objects. Experiment results demonstrate effectiveness of the proposed method.

关键词： Automation Shape Microscopy Conferences Force Process control Robot sensing systems

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Event-triggered state estimation for T-S fuzzy affine systems based on piecewise Lyapunov-Krasovskii functionals

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control Theory and Technology 2019年第1期17卷 99-111页

作者： Meng WANG Jianbin QIU Gang FENG Department of Biomedical Engineering City University of Hong Kong Kowloon Hong Kong China State Key Laboratory of Robotics and Systems & Research Institute of Intelligent Control and Systems Harbin Institute of Technology Harbin Heilongjiang 150080 China

This paper investigates the problem of event-triggered H∞state estimation for Takagi-Sugeno (T-S) fuzzy affine systems. The objective is to design an event-triggered scheme and an observer such that the resulting estimation error system is asymptotically stable with a prescribed H∞performance and at the same time unnecessary output measurement transmission can be reduced. First, an event-triggered scheme is proposed to determine whether the sampled measurements should be transmitted or not. The output measurements, which trigger the condition, are supposed to suffer a network-induced time-varying and bounded delay before arriving at the observer. Then, by adopting the input delay method, the estimation error system can be reformulated as a piecewise delay system. Based on the piecewise Lyapunov-Krasovskii functional and the Finsler's lemma, the event-triggered H∞observer design method is developed. Moreover, an algorithm is proposed to co-design the observer gains and the event-triggering parameters to guarantee that the estimation error system is asymptotically stable with a given disturbance attenuation level and the signal transmission rate is reduced as much as possible. Simulation studies are given to show the effectiveness of the proposed method.

关键词： Takagi-Sugeno (T-S) fuzzy affine systems event-triggered scheme, piecewise Lyapunov-Krasovskii functional, state estimation

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