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16th International Conference on intelligent robotics and Applications, ICIRA 2023

作者： Zhong, Jikang Li, Peng Liu, Xu Zhao, Pinhui Jiang, Han Yang, Liying Li, Decai Bu, Chunguang He, Yuqing 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 Shenyang110169 China University of Chinese Academy of Sciences Beijing100049 China

ISBN: (纸本)9789819964826

In this article, we present a multi-robot continuous ice thickness measurement system that can operate in plateau glacial environments with natural slopes up to 30°, large crevasses of glacier, slippery snow/ice ground surface, and inevitable terrain undulations. The ground station operator can operate the unmanned ground vehicle (UGV) with improved safety driving ability by following the optimal driving advice provided by the driving skill learning model. The air-ground robot collaboration algorithm coordinated the operation of the UGV with the unmanned aerial vehicle (UAV) to improve the mobility of the UGV in complex glacier environments. We obtain multi-scale and multi-aspect environmental information through air-ground collaboration and use a lightweight environmental modeling method to obtain a three-dimensional model of the glacier surface and subglacial terrain. The system was applied in the Korchung Gangri Glacier in the Tibet Plateau in June 2022. The experimental results show that the system can operate in the extreme environment of plateau glaciers and collect high-precision continuous ice thickness distribution data. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Thickness measurement

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AGV semantic attack detection based on extended stochastic Petri net

AGV semantic attack detection based on extended stochastic P...

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作者： Zhang, Sichao Liang, Wei Zhang, Yinlong Wang, Kai 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 Shenyang110169 China University of Chinese Academy of Sciences Beijing100049 China

Semantic attack, as a covert and highly destructive network attack, seriously threatens the security of automatic guided vehicle (AGV) system. To make it worse, the dynamic change of wireless channel makes semantic attack detection more non-intractable. In order to solve the issues on the current semantic attack detection in wireless network environment, this paper proposes an extended stochastic Petri net (ESPN)-based detection method. It builds a stochastic Petri net (SPN) model for the normal operation process of AGV system, and detects the semantic attack by comparing the characteristics of relevance matrix, average dwell time and token density. Additionally, we innovatively add the wireless channel evaluation parameter in the SPN model, to estimate the current wireless channel state and eliminate the impact of wireless interference on attack detection. Eventually, an AGV attack detection system experimental platform has been developed to verify the effectiveness of the proposed method. The experimental results show that the proposed algorithm can effectively eliminate the impact of wireless channel interference on semantic attack detection, and has impressive detection performance. Copyright © 2023 Inderscience Enterprises Ltd.

关键词： Stochastic systems

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An Improved Deep Learning Method-based Detection of Transmission Line Insulator Defects

An Improved Deep Learning Method-based Detection of Transmis...

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2023 International Conference on Computer, Artificial Intelligence, and Control Engineering, CAICE 2023

作者： Gao, Pengpei Song, Chunhe Yu, Shimao Wu, Tingting 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 Shenyang110169 China University of Chinese Academy of Sciences Beijing100049 China

ISBN: (纸本)9781510665040

The insulator is a vital component of power equipment that aids in power transmission. Aiming at transmission line faults caused by missing insulator pieces, this paper proposed to divide insulator detection and defect location into two steps. Additionally, we add Squeeze-and-Excitation (SE) module into the Faster R-CNN model at the insulator detection stage, which could enhance insulator detection accuracy under similar model complexity and also improve the detection efficiency of the YOLOv3 model on insulator defect location. © 2023 SPIE.

关键词： Object detection

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A Framework for Automatic Identification of Neural Network Structural Redundancy Based on Reinforcement Learning 5

A Framework for Automatic Identification of Neural Network S...

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5th International Conference on Computer Information Science and Artificial Intelligence, CISAI 2022

作者： Wu, Tingting Song, Chunhe Zeng, Peng 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 Shenyang110169 China University of Chinese Academy of Sciences Beijing100049 China

ISBN: (纸本)9781510662520

The increasing structure of neural networks makes it difficult to deploy on edge devices with limited computing resources. Network pruning has become one of the most successful model compression methods in recent years. Existing works usually compress models by removing unimportant filters based on the importance. However, the importance-based algorithms tend to ignore the parameters that extract edge features with small criterion values. And recent studies have shown that the existing criteria rely on norm and lead to similar model compression structures. Aiming at the problems of ignoring edge features and manually specifying the pruning rate in current importance-based model pruning algorithms, this paper proposes an automatic recognition framework for neural network structure redundancy based on reinforcement learning. First, we perform cluster analysis on the filters of each layer, and map the filters into a multidimensional space to generate similar sets with different functions. We then propose a criterion for identifying redundant filters within similar sets. Finally, we use reinforcement learning to automatically optimize the cluster dimension, and then determine the optimal pruning rate for each layer to reduce the performance loss caused by pruning. Extensive experiments on various benchmark network architectures and datasets demonstrate the effectiveness of our proposed framework. © 2023 SPIE.

关键词： Reinforcement learning

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A 5G-Based Switching Method between a Local Controller and an Edge Controller 6

A 5G-Based Switching Method between a Local Controller and a...

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6th International Conference on intelligent robotics and Control Engineering, IRCE 2023

作者： Wang, Xiulian Lin, Jinggao Jin, Xi Xia, Changqing Xu, Chi College of Automation and Electrical Engineering Shenyang Ligong University China Chinese Academy of Sciences Key Laboratory of Networked Control Systems Shenyang China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China

ISBN: (纸本)9798350326338

With the rapid development of edge computing, industrial automation has evolved a two-layer distributed computing architecture, including local controllers communicating through wired networks and edge controllers communicating wirelessly. The edge controllers in existing studies use WIFI, which has a limited working distance and requires independent network deployment, so they are unsuitable for future large-scale complex industrial production. At present, 5G technology is undergoing rapid development in the field of industrial automation, with wide coverage and excellent mobility, gradually becoming suitable for future large-scale and complex industrial production scenarios. Therefore, this paper proposed an SW5G method based on 5G, which combined the local controller with the edge controller. The controllers were switched according to the constantly changing 5G network transmission delay, thereby optimizing the overall system control performance. Finally, simulation experiments demonstrated good control performance of SW5G in various network scenarios. © 2023 IEEE.

关键词： Controllers

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Fault Diagnostic Opportunities for Robot Servo Motors Using the Physics of Failure Analysis 14

Fault Diagnostic Opportunities for Robot Servo Motors Using ...

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14th International Conference on Reliability, Maintainability and Safety, ICRMS 2023

作者： Zhang, Bo Liang, Shan Wang, Kai Key Laboratory of Networked Control Systems Shenyang Institute of Automation Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China College of Computer Science and Technology University of Chemical Technology Chinese Academy of Sciences Shenyang China

ISBN: (纸本)9798350329988

Joint robots are widely used in various industries, such as aviation, aerospace, and automotive manufacturing. The performance degradation of servo motors can significantly affect the overall performance of the robots because of the core component of joint robots, and therefore, it is critical to detect and address servo motor failures promptly. In this study, we analyze some common causes and mechanisms of performance degradation in robot servo motors using the physics of failure analysis. We also discuss strategies for detecting and diagnosing faults using these mechanisms before the servo motors fail completely. © 2023 IEEE.

关键词： Servomotors

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Research on Knowledge-based Assembly Process Planning Method Based on Representation Learning Reasoning

Research on Knowledge-based Assembly Process Planning Method...

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Chinese Control and Decision Conference, CCDC

作者： Yu-kai Fu Le-jun Fu Yi-yang Liu Peng Zeng Rui-fei Peng Key Laboratory of Networked Control Systems Shenyang Institute of Automation Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Science Shenyang China

ISBN: (数字)9798350387780

ISBN: (纸本)9798350387797

For multi-variety and small-batch assembly parts, the assembly process updates and iterations are very frequent. The assembly process planning method based on manual experience cannot effectively utilize the large amount of hidden assembly process knowledge generated during product iteration. To solve this problem, this paper proposes an effective assembly process planning method based on knowledge graph. Fristly, the entire assembly is constructed from each layer of assembly components to reduce the computational complexity of assembly process planning. Then, assembly process planning starts from the last layer of assembly components. The entire assembly process planning is obtained by concatenating the results of each layer’s assembly process planning from bottom to top. Assembly operations are determined based on the features of the base component and neighboring assembly components. If there is no corresponding assembly operation for the assembly features, the assembly operation can be inferred through representation learning. After that, arrange and combine all possible assembly solutions to form a feasible solution space. Inferring the optimal assembly process sequence through rules. Combining the optimal assembly sequence with specific assembly operations to complete assembly process planning. Finally, Macro and micro adjustments are made to the assembly process planning of different products in the same series by comparing the differences between current product and classic product. In this paper, the upper door of elevator is used as an example to verify the proposed method. The results show that the proposed method can effectively realize assembly process planning.

关键词： Representation learning Process planning Knowledge based systems Process control Knowledge graphs Manuals Predictive models

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High-precision Calibration of Camera and IMU on Manipulator for Bio-inspired Robotic System

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Journal of Bionic Engineering 2022年第2期19卷 299-313页

作者： Yinlong Zhang Wei Liang Sichao Zhang Xudong Yuan Xiaofang Xia Jindong Tan Zhibo Pang State Key Laboratory of Robotics Shenyang Institute of AutomationChinese Academy of SciencesShenyang 110016China Key Laboratory of Networked Control Systems Chinese Academy of SciencesShenyang 110016China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of SciencesShenyang 110169China The School of Computer Science and Technology Xidian UniversityXi’an 710071China Department of Mechanical Aerospace and Biomedical EngineeringUniversity of TennesseeKonxville 37996USA Department of Automation Technology ABB Corporate Research Sweden72178 VästerasSweden

Inspired by box jellyfish that has distributed and complementary perceptive system,we seek to equip manipulator with a camera and an Inertial Measurement Unit(IMU)to perceive ego motion and surrounding unstructured *** robot perception,a reliable and high-precision calibration between camera,IMU and manipulator is a critical *** paper introduces a novel calibration ***,we seek to correlate the spatial relationship between the sensing units and manipulator in a joint ***,the manipulator moving trajectory is elaborately designed in a spiral pattern that enables full excitations on yaw-pitch-roll rotations and x-y-z translations in a repeatable and consistent *** calibration has been evaluated on our collected visual inertial-manipulator *** systematic comparisons and analysis indicate the consistency,precision and effectiveness of our proposed calibration method.

关键词： Bio-inspired robotic system Monocular camera IMU Manipulator Calibration

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Fault Detection Based on Hierarchical Mode Analysis with ICA-KICA 41

Fault Detection Based on Hierarchical Mode Analysis with ICA...

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第41届中国控制会议

作者： Shuai Li Xiaofeng Zhou Haibo Shi 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 University of Chinese Academy of Sciences

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

For the problem of fault detection in non-Gaussian and nonlinear multimode processes,a fault detection method based on hierarchical mode analysis with independent component analysis(ICA)-kernel independent component analysis(KICA) is *** stable and transition modes coexist in multimode processes and the mode information has uncertainty,hierarchical mode analysis is used for obtaining the hierarchical mode ***,the ICA-KICA is presented for modeling the stable and transition modes obtained from the hierarchical mode ***,a mode identification method based on discriminant function is given for fault *** penicillin fermentation process is used for the experiments of fault detection and the analyses indicate the performance of the fault detection based on hierarchical mode analysis with ICA-KICA.

关键词： Fault detection multimode process hierarchical mode analysis ICA-KICA

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Design of Polar Coding in Filtered-OFDM

Design of Polar Coding in Filtered-OFDM

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International Conference on Internet of Things, Communication and intelligent Technology, IoTCIT 2022

作者： Piao, Jinnan Li, Dong Li, Zhibo Yang, Ming Liu, Jindi Yu, Xueting 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

ISBN: (纸本)9789819904150

The filtered-orthogonal frequency division multiplexing (f-OFDM) is a new waveform configuration for the fifth generation wireless communication system, which satisfies different requirements and channel characteristics more flexibly. Polar codes are adopted as the channel coding scheme of enhance mobile broadband (eMBB) control channel scenario of 5G and is also the candidate coding scheme for ultra-reliable and low latency communications (URLLC) which is on services with strict delay constraints, such as industrial automation. In the paper, we introduce polar codes into f-OFDM system to increase the performance. The conception of channel polarization transformation is extended into the f-OFDM transmission system, where we divide the f-OFDM channels into binary-input channels with a two-stage channel polarization transformation. For the first stage of transformation, we divide a f-OFDM channel into a group of f-OFDM synthesized channels with the bit-interleaved modulation scheme. For the second stage of transformation, we decompose the f-OFDM synthesized channels into binary polarized channels with parallel channels polarization principle. The proposed scheme is evaluated via link simulation under AWGN and fading channels. The simulation results illustrate that the performance gain of polar codes is not affected by the f-OFDM compared with turbo coding scheme. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Orthogonal frequency division multiplexing

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