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Digital Signal Processing and its Applications (DSPA), International Conference on

作者： Yeldos A. Altay Raisa K. Uskenbayeva Abu-Alim E. Ayazbay Alexey V. Fedorov Department of Robotics and Technical Means of Automation Satbayev University Almaty Kazakhstan Institute of Automation and Information Technologies Vice-Rector Satbayev University Almaty Kazakhstan Electronic engineering Almaty University of Power Engineering and Telecomunications Almaty Kazakhstan Faculty of Control Systems and Robotics ITMO University Saint-Petersburg Russian Federation

ISBN: (数字)9798331518752

ISBN: (纸本)9798331518769

In this scientific article under consideration, a machine learning model has been developed that allows predicting the impact of filter parameters on the accuracy of measuring a biosignal - an ECG (electrocardiography) signal. For the first time, quantitative results have shown the degree of influence and the error introduced into the measured biosignal and described through dependence. The results of assessing the obtained relationship of indicators demonstrate an inverse correlation relationship that characterizes a decrease in the accuracy of measurement at the output of a high-order digital filtering system. The machine learning model is based on the linear regression method the dependence of which is approximated by the method based on least squares and visualized using a scattergram. The adequacy of the developed machine learning model was confirmed by calculating the coefficient of determination and checking its statistical significance. The developed model can be used to create new or improve existing biomedical data processing systems to increase the reliability of the results.

关键词： Accuracy Shape Filtering Biological system modeling Machine learning Biomedical measurement Electrocardiography Distortion Distortion measurement Digital filters

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Renderable Street View Map-Based Localization: Leveraging 3D Gaussian Splatting for Street-Level Positioning

Renderable Street View Map-Based Localization: Leveraging 3D...

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IEEE/RSJ International Conference on Intelligent Robots and systems (IROS)

作者： Howoong Jun Hyeonwoo Yu Songhwai Oh Artificial Intelligence (IPAI) Seoul National University and Automation and Systems Research Institute (ASRI) and Sequor Robotics Inc. Seoul Korea Republic of Department of Intelligent Robotics & Mechanical Engineering Sungkyunkwan University (SKKU) Suwon-si Korea Republic of Department of Electrical and Computer Engineering (ECE) & Interdisciplinary Program in Artificial Intelligence (IPAI) Seoul National University and Automation and Systems Research Institute (ASRI) and Sequor Robotics Inc. Seoul Korea Republic of

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

In this paper, we introduce a new method that first utilizes 3D Gaussian splatting in street-level localization problem. Robust localization with street-level real-world images such as street view is a major issue for autonomous vehicle, augmented reality (AR) navigation, and outdoor mobile robots. The objective is to determine the position and orientation of a query image that matches a street view database composed of RGB images. However, given the limited information available in the street view images, accurately determining the location solely based on this data presents a significant challenge. To address this challenge, we propose a novel method called renderable street view map-based localization (RSM-Loc). This approach enhances the localization process by augmenting 2D street view images into a renderable 3D map using 3D Gaussian splatting, to resolve street-level localization problems. Upon receiving a query RGB image without geometry information, the proposed method renders 2D images from a pre-made renderable map and compares image pose similarities between the rendered images and the query image. Through iterations of this process, the proposed method eventually estimates the pose of the given query image. The experimental results demonstrate that RSM-Loc outperforms the baselines with neural-field-based localization. Additionally, we conduct deep analysis on the proposed method to show that our method can serve as a new concept for the street-level localization problem.

关键词： Location awareness Visualization Matched filters Three-dimensional displays Image resolution Navigation Noise measurement Mobile robots Intelligent robots Image reconstruction

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Transmission Optimization Based on Industrial Internet Information Model 4

Transmission Optimization Based on Industrial Internet Infor...

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4th International Conference on Machine Learning and Computer Application, ICMLCA 2023

作者： Feng, Haiwen Tian, Hao Wang, Ting Zhu, Jingyang Wang, Xintong School of Software College Shenyang University of Technology Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences 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)9798400709449

With the standardized development of industrial Internet, the communication among industrial Internet platforms, devices and gateways is more frequent. Due to the problems of heterogeneous data and low data interoperability existing in different devices, the communication between industrial Internet is hindered. With the development of industrial Internet information model, on the basis of reducing data heterogeneity and improving interoperability, it is more difficult to transmit information due to the increase of information content. Therefore, this paper will design an information model transmission optimization method, through the information model XML file content optimization compression, while in the information model may exist in the Chinese information processing, so that it can better compress the Chinese-English information. The results show that the XML file used in information transmission can be compressed by using this optimization method, and it is proved that the proposed optimization method can improve the transmission efficiency. © 2023 ACM.

关键词： Interoperability

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Stackelberg Game-Based Optimal Scheduling Strategy for Multi-Microgrid systems with Electricity-Heat Shared Energy Storage

Stackelberg Game-Based Optimal Scheduling Strategy for Multi...

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Chinese automation Congress (CAC)

作者： Chao Peng Decai Zhang Mian Hu Huaiyu Wu Yang Chen Engineering Research Center for Metallurgical Automation and Measurement Technology of Ministry of Education Wuhan University of Science and Technology Institute of Robotics and Intelligent Systems Wuhan University of Science and Technology

ISBN: (数字)9798350368604

ISBN: (纸本)9798350368611

To address the challenges of the complexity of electricity-heat coupling, the pollution of carbon emissions, the security of privacy information, and the uncertainty of renewable energy generations (REGs), this paper proposes a novel multi-microgrid electricity-heat shared energy storage system framework, considering that the integrated energy storage operator (IESO) is equipped with electric boiler and two types of energy storage (i.e., electrical energy storage and heat energy storage) devices, and each microgrid (MG) is equipped with combined heat and power system that coupled carbon capture system and power-to-gas device. Latin hypercube sampling is used to deal with the uncertainty of REGs. A distributed bi-level iterative algorithm based on Stackelberg game theory is designed, which effectively protects the users' privacy information, and finally a Stackelberg equilibrium strategy is obtained, where the IESO and each MG minimize its operating cost. Simulation results show that the proposed optimal scheduling strategy can effectively reduce the operating cost and carbon emissions of each MG, and increase the benefits of the IESO.

关键词： Privacy Uncertainty Costs Cogeneration Optimal scheduling Microgrids Thermal pollution Iterative methods Energy storage Resistance heating

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Flexible job shop machines and AGVs cooperative scheduling on the basis of DQN algorithm

Flexible job shop machines and AGVs cooperative scheduling o...

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IEEE Advanced Information Management,Communicates,Electronic and automation Control Conference (IMCEC)

作者： Dong Xiaoting Wan Guangxi Zeng Peng State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Key Laboratory of Networked Control Systems Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Shenyang China University of Chinese Academy of Sciences Beijing China

ISBN: (数字)9798350316537

ISBN: (纸本)9798350316544

In flexible job shop, the transportation time and path of Automated Guided Vehicles (AGVs) greatly impact the production cycle time. However, traditional flexible job shop scheduling problems (FJSSP) mainly focus on job sequencing and machine selection, neglecting the effect of AGVs transportation on the production process. This often leads to suboptimal scheduling solutions that are difficult to guide the shop floor operation effectively. To address this issue, this paper formulates a cooperative scheduling model that integrates the AGVs scheduling into traditional flexible job shop scheduling problem, abbreviated as the FJSMAS problem, with the objective of makespan minimization. Furthermore, by designing state features, action space, and reward function, the FJSMAS problem is transformed into a Markov decision process, a deep reinforcement learning algorithm (DRL) is then adopted to solve it. The feasibility of the proposed FJSMAS model and the effectiveness of DRL algorithm in solving the FJSMAS problem are verified through benchmark’s instances.

关键词： Greedy algorithms Sequential analysis Job shop scheduling Remotely guided vehicles Transportation Production Benchmark testing

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automation of Life Data Analysis Processes 13

Automation of Life Data Analysis Processes

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13th International DAAAM Baltic Conference and 29th International Baltic Conference, BALTMATTRIB 2021

作者： Krämer, Jonathan Thiele, Gregor Johanni, Theresa Krüger, Jörg Department for Industrial automation The Institute for Machine Tools and Factory Management Technical University of Berlin Germany Department for Process automation and Robotics Fraunhofer Institute for Production Systems and Design Technology Germany

Life data analysis is an effective statistical process to gain information on the reliability of technical facilities. The Weibull analysis is a widely-used method for modeling the probabilities of different functional failures. For its application in modern manufacturing and maintenance processes, an automation of this analysis is expedient. An exemplary process of data collection and fitting of a parametric model with continuous time scale is analyzed in this article. Its automation with different statistic software tools is described and comparatively evaluated. With the ambition of minimizing manual effort in the process, a highly automated solution was developed in this research. We describe this self-implemented solution in "R" and justify that this procedure automatizes the process more than the examined commercial implementations. The here presented work proves to be a practical real-time assistance, right now applied in aircraft maintenance. © 2021 DAAAM International. All rights reserved.

关键词： automation

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Fractional-order global fast terminal sliding mode control strategy for fractional-order hydraulic turbine regulating system

Fractional-order global fast terminal sliding mode control s...

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第42届中国控制会议

作者： Shiyu Xi Zhihuan Chen Engineering Research Center for Metallurgical Automation and Measurement Technology of Ministry of Education Institute of Robotics and Intelligent Systems Wuhan University of Science and Technology

Hydraulic turbine regulating system(HTRS) directly affects the safety and stability of hydro-generator units. In this paper, the control and modeling problems of the HTRS are mainly investigated based on the fractional-order theory, aiming to design a novel control strategy to raise the dynamic response of the HTRS and ensure the frequency stability of the hydrogenerator units. Firstly, a nonlinear model of the fractional-order HTRS is established mathematically. Secondly, a fractionalorder global fast terminal sliding mode controller is designed to improve the dynamic performance as well as the robustness of the system. Finally, relevant simulations are carried out to illustrate the effectiveness and rationality of the proposed control strategy in comparison with two other fractional-order control strategies.

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Design and Implementation of OpenWSN Hardware Platform 2

Design and Implementation of OpenWSN Hardware Platform

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2nd International Conference on Algorithms, High Performance Computing and Artificial Intelligence, AHPCAI 2022

作者： Zhang, Shusheng Xie, Chuang Liu, Jun Zhao, Chun Yang, Zhijia Mao, Jizhi College of Automation and Electrical Engineering Shenyang Ligong University Shenyang110159 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 Shenyang110169 China

ISBN: (纸本)9798350334784

This paper proposes a new wireless sensor network hardware platform based on OpenWSN project launched by the University of California, Berkeley. The hardware platform's processor uses a 32-bit microcontroller (STM32F103RCT6) produced by STMicroelectronics (ST), and the wireless module uses the WISA470 chip. The final experimental results show that this platform can support the Open WSN project very well. © 2022 IEEE.

关键词： Wireless sensor networks

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Zero-Shot Kidney Stone Segmentation Based on Segmentation Anything Model for Robotic-Assisted Endoscope Navigation 16th

Zero-Shot Kidney Stone Segmentation Based on Segmentation A...

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

作者： Meng, Hui Chen, Lingkai Zhu, Shiqiang Fei, Chentao Zhang, Yong Zheng, Miaojuan Han, Jianda Song, Wei School of Intelligent Science and Technology Hangzhou Institute for Advanced Study University of Chinese Academy of Sciences 1 Sub-lane Xiangshan Hangzhou310024 China Research Center for Intelligent Robotics Research Institute of Interdisciplinary Innovation Zhejiang Laboratory Hangzhou311100 China Hangzhou ElephantChain Network Technology Co. Ltd. Hangzhou China Faculty of Mechanical Engineering and Automation Zhejiang Sci-Tech University Hangzhou310018 China College of Artificial Intelligence and Tianjin Key Laboratory of Intelligent Robotics Institute of Robotics and Automatic Information Systems Nankai University Tianjin300350 China

ISBN: (纸本)9789819964888

Biomedical robotics has had a significant impact on flexible ureteroscopy (FURS) for the management of nephrolithiasis. The biomedical robots provide a suitable and safe platform for FURS. However, operating the robots expertly still represents a challenge for surgeons. Vision-based navigation is an effective means to simplify the operations of robots by surgeons, which has great potential to improve surgical efficiency. To achieve vision-based navigation, the localization of kidney stones in endoscopic images is the first step. In this paper, we propose a stone segmentation method (SSM) based on zero-shot learning, which consists of segmentation anything model (SAM), an image preprocessing module, and a mask postprocessing module. The SAM segments all objects in endoscopic images, which lack semantic information. The preprocessing module is designed to suppress interference of reflective area in endoscopic images, and the mask postprocessing module is used to filter noise masks. The experimental results on our collected endoscopic images indicate that our method achieves close accuracy on stone segmentation compared with supervised U-Net and VGG_U-Net, which significantly outperforms the Ostu and the SAM. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.

关键词： Endoscopy

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Multi-objective optimal design of an optimal fuzzy fractional order PID controller for fractional order hydraulic turbine regulating system

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Expert systems with Applications 2025年 286卷

作者： Xi, Shiyu Chen, Zhihuan Engineering Research Center for Metallurgical Automation and Measurement Technology of Ministry of Education Wuhan430081 China Institute of Robotics and Intelligent Systems Wuhan University of Science and Technology Wuhan430081 China

The hydraulic turbine regulating system (HTRS) is a crucial component of the energy dispatch of hydropower plants. To achieve precise control of the HTRS output speed under variable working conditions, this paper explores the benefits of multi-objective optimization in the control field. A multi-objective optimization problem is established for an optimal fuzzy fractional order PID (OFFOPID) controller, tailored for fractional order HTRS working under both unload and load conditions. By introducing fractional order calculus operators and specifically optimizing the gains, rule bases, and membership functions, the OFFOPID controller enhances the traditional fuzzy PID controller and provides greater flexibility. In this multi-objective optimization problem, steady-state error (SSE), integral square error (ISE), and overshoot percentage (OP) are selected as the objective functions to ensure precise control accuracy, rapid response, and smooth transient behavior. To obtain the optimal Pareto frontier, the Pareto local search-nondominated sorting genetic algorithm III (PLS-NSGAIII) is proposed, with hybrid coding for population individuals specific to the OFFOPID framework. In this algorithm, the improved individual selection, crossover, and mutation operators enhance global search, while individual local search, conducted based on Pareto optimality, improves local search capabilities. Experiments show that the OFFOPID controller provides rapid and accurate responses for highly inertial HTRS, outperforming traditional controllers. Compared to three other multi-objective optimization algorithms on benchmark test functions and HTRS applications, the PLS-NSGAIII achieves lower GD and IGD values and higher HV values, demonstrating its effectiveness in solving HTRS problem. © 2025 Elsevier Ltd

关键词： Multiobjective optimization

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