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Image Processing, Computer Vision and Machine Learning (ICICML), International Conference on

作者： Shimao Yu Chunhe Song Yong Sun Pengpei Gao Key Laboratory of Networked Control Systems Shenyang Institute of Automation 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

ISBN: (数字)9798350355413

ISBN: (纸本)9798350355420

In the process of mining company beneficiation, large rotating equipment, pipelines and electrical equipment have many complex inspection areas and diverse inspection contents. The lack of intelligent solutions to the problem of pipeline leakage will cause serious consequences such as equipment shutdown if it is not found in time. This paper proposes a lightweight yolov5 intelligent leakage inspection method for the magnetic mill workshop. The inspection robot is used to continuously collect images of possible leakage points and transmit them to the background server. The improved yolov5 algorithm simplifies the model structure and realizes rapid and accurate identification of leakage targets with limited computing resources. The computational efficiency is increased by 44.98% with almost no loss of model accuracy. The mAP_0.5 of identifying large targets at leakage points reaches 97.96%.

关键词： YOLO Training Accuracy Conferences Magnetic resonance imaging Computational modeling Pipelines Inspection Servers Monitoring

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Design and Implementation of Industrial Real-Time Ethernet Redundant Network Based on Parallel Redundancy Protocol

Design and Implementation of Industrial Real-Time Ethernet R...

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Computer Science, Electronic Information Engineering and intelligent control Technology (CEI), IEEE International Conference on

作者： Mingxu Gang Bingjun Yan Bo Hu 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

ISBN: (数字)9798350372052

ISBN: (纸本)9798350372069

Industrial real-time Ethernet technology is widely used in modern industrial control systems due to its high communication rate and low application cost. However, in complex network environments, industrial real-time Ethernet may encounter data collisions, data loss, and other issues, which reduce the overall reliability of industrial control systems. To address these issues, a method for designing and implementing industrial real-time Ethernet redundancy networks based on parallel redundancy protocols is proposed. The method first analyzes the redundant data frame structure, dual-connected node (DANP) structure, and redundancy implementation principle of parallel redundancy protocols (PRP). Then, aiming at the standard redundancy discard algorithm principle and its shortcomings, an improved sliding window redundancy discard algorithm is proposed to adapt to complex network environments. Based on the discard algorithm, dual-connected redundancy nodes are designed and implemented. Finally, the dual-connected redundancy nodes are used as the core to construct industrial real-time Ethernet redundancy networks. The test results show that in a PRP-based industrial real-time Ethernet redundant network, when a single redundant network fails, the system can switch without delay, greatly improving the reliability of the industrial control system communication network

关键词： Protocols Industrial control Computer network reliability Redundancy Ethernet Complex networks Reliability engineering

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Development of Method for Generating Trajectories of Movement of End Effectors and control Programs for Industrial Robots in an Uncertain Working Environment

Development of Method for Generating Trajectories of Movemen...

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2021 International Russian automation Conference, RusAutoCon 2021

作者： Yukhimets, Dmitry Gubankov, Anton Mursalimov, Eduard Institute of Automation and Control Processes Robotic Laboratory Vladivostok Russia Far Eastern Federal University Dept. of Automation and Robotics Vladivostok Russia Institute of Marine Technology Problems Laboratory of Intelligent Information Systems for Marine Robots Vladivostok Russia

ISBN: (纸本)9780738131566

the deals with the implementation of the method of the trajectories generating for end effectors and control programs for industrial robots in an uncertain working environment. To generate correct trajectories, it is proposed to sequentially process data from vision systems, correct them in the human-machine interface, generate a control program in a generalized form using universal commands and then translate it into the form that a specific industrial robot requires. Experimental studies of the proposed method were carried out, which confirmed the operability and effectiveness of the proposed method. © 2021 IEEE.

关键词： Trajectories

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AGV State Monitoring Based on Global and First-person View Fusion in Digital Workshops 12

AGV State Monitoring Based on Global and First-person View F...

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12th International Conference on CYBER Technology in automation, control, and intelligent Systems, CYBER 2022

作者： Zhang, Sichao Liang, Wei Li, Gengyu Yuan, Xudong An, Haibo Zhang, Yinlong State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 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 Shenyang110169 China University of Chinese Academy of Science Beijing100049 China School of Information and Control Engineering Shenyang Jianzhu University Shenyang110168 China Science and Technology on Information Systems Engineering Laboratory The 28th Research Institute of Cetc Jiangsu Nanjing210007 China

ISBN: (数字)9781665472678

ISBN: (纸本)9781665472678

AGV state monitoring is becoming increasingly important for production system safety in digital workshops. This paper develops a global and first-person view fusion to monitor the AGV (Automated Guided Vehicle) running state in the complex digital workshops. Based on the affine transformation model, the AGV running states, i.e., position, velocity and orientation are estimated by the global camera with the assistance of ArUco markers, which are pasted on the front side of the AGV. Besides, the first-person view camera is used to implement pedestrian detection and distance measurement based on the YOLOv3 model. It is noticeable that the pitch angle is considered for distance measurement, and an improved triangular model for distance measurement is proposed. The effectiveness of the proposed method has been verified in our built platform. © 2022 IEEE.

关键词： Cameras

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Research on prefabricated component production line mold platform combination method

Research on prefabricated component production line mold pla...

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2021 International Conference on Advanced Manufacturing Technology and Electronic Information, AMTEI 2021

作者： Han, Zhonghua Yu, Lingfeng Li, Bo Qi, Yuanwei School of Information and Control Engineering Shenyang Jianzhu University Shenyang110168 China 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

In traditional prefabricated component manufacturing enterprises, there are often problems such as low utilization rate of the platform surface due to poor production plans of the enterprise, resulting in waste of production resources and low production capacity of the enterprise. In order to solve the problem of mold platform combination allocation in the production process of prefabricated component manufacturers, a mold platform combination allocation method based on the combination of machine learning and backtracking is proposed. The backtracking method is used to search for the theoretical best fit combination result, and the improved BL is used. The positioning algorithm simulates the placement process of the mold on the platform, and uses the Apriori algorithm to train the obtained data set to obtain the association rules contained in the frequent item set. When the enterprise re-produces, the prefabricated components are combined according to the association rules for production, and the utilization rate of the platform is improved. The simulation test is carried out with the example data of the prefabricated component manufacturing enterprise, which verifies the effectiveness of the combination allocation method of mold and platform combined with the backtracking method and the Apriori algorithm to solve the problem. © Published under licence by IOP Publishing Ltd.

关键词： Production control

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K-BMPC: Derivative-based Koopman Bilinear Model Predictive control for Tractor-Trailer Trajectory Tracking with Unknown Parameters

arXiv

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arXiv 2023年

作者： Wang, Zehao Zhang, Han Wang, Jingchuan Department of Automation Institute of Medical Robotics Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240 China

Nonlinear dynamics bring difficulties to controller design for control-affine systems such as tractor-trailer vehicles, especially when the parameters in the dynamics are unknown. To address this constraint, we propose a derivative-based lifting function construction method, show that the corresponding infinite dimensional Koopman bilinear model over the lifting function is equivalent to the original control-affine system. Further, we analyze the propagation and bounds of state prediction errors caused by the truncation in derivative order. The identified finite dimensional Koopman bilinear model would serve as predictive model in the next step. Koopman Bilinear Model Predictive control (K-BMPC) is proposed to solve the trajectory tracking problem. We linearize the bilinear model around the estimation of the lifted state and control input. Then the bilinear Model Predictive control problem is approximated by a quadratic programming problem. Further, the estimation is updated at each iteration until the convergence is reached. Moreover, we implement our algorithm on a tractor-trailer system, taking into account the longitudinal and side slip effects. The open-loop simulation shows the proposed Koopman bilinear model captures the dynamics with unknown parameters and has good prediction performance. Closed-loop tracking results show the proposed K-BMPC exhibits elevated tracking precision with the commendable computational efficiency. The experimental results demonstrate the feasibility of K-BMPC. © 2023, CC BY-NC-SA.

关键词： Model predictive control

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intelligent Vision-Assisted Obstacle Avoidance and Unknown Seasonal Products Navigation in Farmer's Market for the Visually Impaired

SSRN

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SSRN 2023年

作者： Liu, Mei Chen, Yunhua Djoulde, Aristide He, Mengfan Rao, Jinjun Giernacki, Wojciech Wang, Zhiming Chen, Jinbo Shanghai Key Laboratory of Intelligent Manufacturing and Robotics School of Mechatronic Engineering and Automation Shanghai University Shanghai200444 China Institute of Robotics and Machine Intelligence Faculty of Control Robotics and Electrical Engineering Poznan University of Technology Piotrowo 3a Poznan60-965 Poland

Abstract: Shopping at a farmer's market is a considerable daily challenge for the visually impaired. General indoor obstacle avoidance and navigation algorithms are not fully applicable to the crowded and dynamic shopping environment of farmer's market. To overcome these challenges and provide precise assistance to visually impaired, this paper proposes an intelligent vision-assisted (IVA) algorithm for navigating narrow and crowded farmer's market aisles. The algorithm employs a pedestrian detection camera based on deep learning as the hardware to intelligently detect the type and number of pedestrians in front, and guides a navigation robot to adopt corresponding obstacle avoidance strategies in time according to the detection results. Different from general obstacle avoidance methods, IVA doesn't have issues of guiding robot to make frequent turns and change routes when avoiding obstacles in a crowded and narrow environment, making it more suitable for the visually impaired. Additionally, this paper proposes an unknown seasonal product navigation (USPN) algorithm for robots to automatically search for navigation information that has changed. When used in conjunction with a camera driven by deep learning, USPN successfully guided a navigation robot to identify the names and coordinates of newly listed products. Compared with general navigation algorithms, USPN can guide robots to update product information timely and intelligently. Experimental tests conducted in a farmer's market demonstrated that IVA is more intelligent and efficient than the dynamic window approach (DWA) in obstacle avoidance performance, and it is more suitable for guiding the visually impaired;furthermore, USPN successfully guides the robot to automatically acquire products information that changes with the seasons, and the acquired product categories and locations are precise. Particularly, IVA and USPN can be used as references when designing guide robots for use in public spaces like super

关键词： Navigation

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Research on optimization method of routing buffer linkage based on Q-learning

Research on optimization method of routing buffer linkage ba...

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2021 International Conference on Advanced Manufacturing Technology and Electronic Information, AMTEI 2021

作者： Han, Zhonghua Qi, Hongfeng Chang, Daliang Gong, Wei Dai, Shilong School of Information and Control Engineering Shenyang Jianzhu University Shenyang110168 China 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

According to the characteristics of the painting process of passenger car manufacturing enterprises, by formulating the routing buffer linkage rules based on the total renewal cost, the linkage process of the bus in the routing buffer is controlled, and an improved Q-learning (Q- The routing buffer of learning) algorithm quickly finds the optimal path method. According to the actual production situation, this method improves the dynamic parameters of the algorithm on the basis of the traditional Q-learning algorithm, and improves the optimization speed and accuracy of the algorithm by establishing the correlation between the work-in-process and its neighboring work-in-process in the current state. Through multiple sets of example simulation tests, the effectiveness of the Q-learning algorithm in solving the optimization problem of routing buffer linkage is verified. © Published under licence by IOP Publishing Ltd.

关键词： Learning algorithms

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A DDOS Attack Traffic Classification Model for Industrial Internet Based on CNN-LSTM

A DDOS Attack Traffic Classification Model for Industrial In...

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2022 Chinese automation Congress, CAC 2022

作者： Wei, Weixuan Liu, Xianda Sheng, Chuan Feng, Ansong Shenyang University of Chemical Technology College of Information Engineering Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China

ISBN: (纸本)9781665465335

With the continuous development and application of industrial Internet, the weakness of the security defense capability of industrial Internet has become increasingly prominent. This paper presents an end-to-end classification model combining Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) network for DDoS attacks over industrial Internet. By self-learning the spatial and temporal characteristics of the original attack traffic, the model can avoid subjective errors that may occur due to manual selection of features. This method is a feasible means, with an accuracy rate of 99%. © 2022 IEEE.

关键词： Long short-term memory

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Design of a Novel Autonomous Docking System With a Supporting Robotic Fish

Design of a Novel Autonomous Docking System With a Supportin...

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2023 IEEE International Conference on Real-Time Computing and robotics, RCAR 2023

作者： Dong, Huijie Zhao, Chunyang Qiao, Tiezhu Wang, Jian Chen, Di Meng, Yan Yu, Junzhi Taiyuan University of Technology Key Laboratory of Advanced Transducers and Intelligent Control System Ministry of Education Taiyuan030024 China Chinese Academy of Sciences Laboratory of Cognitive and Decision Intelligence for Complex System Institute of Automation Beijing100190 China Peking University State Key Laboratory for Turbulence and Complex Systems Department of Advanced Manufacturing and Robotics College of Engineering Beijing100871 China Guangdong Ocean University College of Electronics and Information Engineering Zhanjiang524088 China

ISBN: (纸本)9798350327182

Underwater supporting robots serving as a relay of energy supplements and communication for other underwater equipment are promising for ocean exploration, development, and protection. This paper proposes a novel autonomous docking system centered on a designed supporting robotic fish named 'CourierFish'. Specifically, CourierFish is capable of docking with a surface dock station for supplying itself and docking with a seafloor platform for supporting equipment in the platform. A visual navigation scheme integrating LED and ArUco markers is presented for accurate localization. The control approach for docking motion is also illustrated. Simulations and aquatic experiments are performed to verify the feasibility of the proposed docking system. The obtained results lay a solid foundation for the construction of various underwater equipment and robot networks. © 2023 IEEE.

关键词： Fish

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