检索结果-内蒙古大学图书馆

Computer Engineering and Intelligent control (ICCEIC) International Conference on

作者： Yue Zhang Yong Sun Chunhe Song Pengpei Gao State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China

ISBN: (数字)9798331507992

ISBN: (纸本)9798331508005

In modern container cloud computing environments, achieving efficient elastic scaling is crucial to optimizing resource utilization and improving system performance. This paper proposes a new prediction model based on gated recurrent unit (GRU) and attention mechanism for load prediction and elastic scaling strategy optimization. The model uses the time series processing capability of GRU combined with the optimization characteristics of the attention mechanism to improve the accuracy and real-time performance of load prediction. Experimental results show that compared with traditional methods, the model can more accurately capture the load change trend and achieve more agile and efficient resource scheduling and management, thereby effectively reducing resource waste and improving service quality. This study provides a novel and effective solution for elastic scaling in container cloud environments.

关键词： Cloud computing Attention mechanisms Computational modeling System performance Time series analysis Containers Predictive models Resource management Optimization Load modeling

来源：评论

学校读者我要写书评

暂无评论

PS-Loc: Robust LiDAR Localization with Prior Structural Reference

PS-Loc: Robust LiDAR Localization with Prior Structural Refe...

引用

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

作者： Rui Li Wentao Zhao Tianchen Deng Yanbo Wang Jingchuan Wang Institute of Medical Robotics Department of Automation Shanghai Jiao Tong University Ministry of Education Key Laboratory of System Control and Information Processing Shanghai China

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

Prior structural reference like floor plan is readily accessible in indoor scene, which exhibits the potential of improving localization quality without the requirements of a previously-built high-precision map. This paper introduces a novel optimal transport-based framework for prior structural reference-based localization, aiming to improve the robustness for the robot localization. Leveraging the spacial relations of structures, a matching method based on optimal transport theory is proposed and it improves the robustness of matching results in dynamic scene and rapid rotation conditions. Additionally, this paper handles metric inaccuracies in the known structural reference by implementing an prior guided plane adjustment-based updating strategy. This strategy combines prior and observational information to jointly optimize the structural information within a sliding window. The performance of the framework is validated through real-world experiments, demonstrating superior accuracy and robustness to disturbances from dynamic occlusion and rapid rotation compared to common state-of-the-art SLAM and localization methods.

关键词： Location awareness Measurement Laser radar Simultaneous localization and mapping Accuracy Robustness Robot localization Intelligent robots Floors

来源：评论

学校读者我要写书评

暂无评论

Design and Implementation of OpenWSN Hardware Platform 2

Design and Implementation of OpenWSN Hardware Platform

引用

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

来源：评论

学校读者我要写书评

暂无评论

RoboFold: A platform for Protein-folding Inspired Robot Swarms ∗ 5

RoboFold: A platform for Protein-folding Inspired Robot Swar...

引用

5th World Robot Conference Symposium on Advanced robotics and automation, WRC SARA 2023

作者： Zhang, Feng Gu, Yuping Yuan, Shuai Yang, Yongliang Shenyang Jianzhu University School of Electrical and Control Engineering Liaoning Shenyang110168 China Shenyang Institute of Automation Chinese Academy of Sciences State Key Laboratory of Robotics Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Liaoning Shenyang110016 China Shenyang Jianzhu University School of Computer Science and Engineering School of Electrical and Control Engineering Liaoning Shenyang110168 China

ISBN: (纸本)9798350307320

Natural swarms have inspired various controlling algorithms for swarm robotics, while few of them were programmed in a similar way as the natural swarms. Defining a reliable programming method is still a daunting challenge in swarm robotics. In nature, the information of 3D protein structure is programmed in the sequence of amino acids of the protein. To mimic the programming method of protein folding, we present a platform for investigating protein-folding inspired programming method for robot swarms. This platform includes three parts: a vibration machine, protein-like robot sequences, and recording devices. The preliminary results presented here demonstrated the effectiveness of this platform and the feasibility of protein-folding inspired programming method for robot swarms. © 2023 IEEE.

关键词： Protein folding

来源：评论

学校读者我要写书评

暂无评论

A Novel Deep Learning Representation for Industrial control System Data

引用

Intelligent automation & Soft Computing 2023年第6期36卷 2703-2717页

作者： Bowen Zhang Yanbo Shi Jianming Zhao Tianyu Wang Kaidi Wang Key Laboratory of Networked Control Systems Chinese Academy of SciencesShenyang110016China Shenyang Institute of Automation Chinese Academy of SciencesShenyang110016China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of SciencesShenyang110169China Shenyang Aircraft Corporation Shenyang110850China Molarray Research TorontoL4B3K1Canada

Feature extraction plays an important role in constructing artificial intel-ligence(AI)models of industrial control systems(ICSs).Three challenges in this field are learning effective representation from high-dimensional features,data heterogeneity,and data noise due to the diversity of data dimensions,formats and noise of sensors,controllers and ***,a novel unsupervised learn-ing autoencoder model is proposed for ICS data in this *** traditional methods only capture the linear correlations of ICS features,our deep industrial representation learning model(DIRL)based on a convolutional neural network can mine high-order features,thus solving the problem of high-dimensional and heterogeneous ICS *** addition,an unsupervised denoising autoencoder is introduced for noisy ICS data in *** the denoising autoencoder allows the model to better mitigate the sensor noise *** this way,the represen-tative features learned by DIRL could help to evaluate the safety state of ICSs more *** tested our model with absolute and relative accuracy experi-ments on two large-scale ICS *** with other popular methods,DIRL showed advantages in four common indicators of AI algorithms:accuracy,precision,recall,and *** study contributes to the effective analysis of large-scale ICS data,which promotes the stable operation of ICSs.

关键词： Industrialcontrolsystem machinelearning deeplearning autoencoder

来源：评论

学校读者我要写书评

暂无评论

Multimodal Perception for Indoor Mobile robotics Navigation and Safe Manipulation

引用

IEEE Transactions on Cognitive and Developmental Systems 2024年

作者： Zhang, Yinlong Liu, Yuanhao Liu, Shuai Liang, Wei Wang, Chu Wang, Kai Chinese Academy of Sciences Key Laboratory of Networked Control Systems Shenyang Institute of Automation Shenyang110016 China Chinese Academy of Sciences State Key Laboratory of Robotics Shenyang Institute of Automation Shenyang110016 China University of Chinese Academy of Sciences Beijing101408 China

Indoor mobile robotics (IMR) has gained significant attention due to its potential applications in various domains, such as healthcare, logistics, and domestic assistance. However, navigating through indoor environments and performing safe manipulations still pose intractable challenges in terms of navigation accuracy and obstacle avoidance. To solve these issues, this paper presents an Artificial Intelligence (AI) embodied multimodal perception framework for IMR intelligent navigation and safe manipulation. To ensure the navigation accuracy and robustness, we employ the complementary forward RGB camera, downward QR vision sensor, and wheel encoder measurements in a unified framework. The visual residuals and wheel odometry residuals are jointly minimized to estimate the robot states. To guarantee the safety of robotic manipulation tasks, we have developed an AI model that integrates transformer network with convolutional neural network, to associate the long-range RGB & depth patches and aggregate the multi-scale obstacle features, enabling the precise detection and segmentation of obstacles in RGB-D images. Afterwards, the depths of detected obstacles are regressed, providing the robot with crucial information for collision avoidance. Eventually, we design a refined robot manipulation system that dynamically adjusts the robot behavior to ensure effective collision avoidance and to minimize potential damage to its mechanical components by constantly evaluating the spatial relationships between the robot and its surroundings. By incorporating advanced obstacle detection and the avoidance mechanism, mobile robots can navigate reliably in indoor environments with a reduced risk of collisions and real-time decision making. The presented method has been evaluated on the developed IMR platform. On the collected dataset, the estimated IMR absolute position and orientation errors are less than 0.18m and 5° respectively. Besides, it achieves 89% mAP on obstacle detection. T

关键词： Image segmentation

来源：评论

学校读者我要写书评

暂无评论

Development of an Industrial Real-time Ethernet Protocol Stack Based on SoC

Development of an Industrial Real-time Ethernet Protocol Sta...

引用

2022 International Symposium on Networks, Computers and Communications, ISNCC 2022

作者： Zhang, Bo Yan, Bingjun Liu, Mingzhe Hu, Bo Xu, Aidong Wang, Kai Key Laboratory of Networked Control Systems Chinese Academy of Sciences China Shenyang Institute of Automation Chinese Academy of Sciences China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences China

ISBN: (数字)9781665485449

ISBN: (纸本)9781665485449

In order to improve the real-time and reliability of network communication in intelligent ship system, this paper analyzes the requirements of ship-borne network, and develops a real-time Ethernet protocol stack based on Zynq7000 series SoC chip. The development of the protocol stack includes the software layer and the firmware layer. As the main part of the protocol stack, the software layer adds real-time communication entities upon the data link layer of the Ethernet reference model, and the timing of communication is controlled by the synchronous precise measurement clock to realize the real-time scheduling and transmission of data. On the other hand, the PTP message timestamp function of clock synchronization and the redundant function of zero recovery time based on PRP algorithm is realized on the firmware layer. Finally, the real-time, reliability and synchronization accuracy of the protocol stack are tested and verified on the developed real-time Ethernet cards. © 2022 IEEE.

关键词： System-on-chip

来源：评论

学校读者我要写书评

暂无评论

NA-CPG: A robust and stable rhythm generator for robot motion control

引用

Biomimetic Intelligence & robotics 2022年第4期2卷 30-38页

作者： Ru Tong Changlin Qiu Zhengxing Wu Jian Wang Min Tan Junzhi Yu State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China Department of Advanced Manufacturing and Robotics College of EngineeringPeking UniversityBeijing 100871China

Central pattern generators(CPGs)have been widely applied in robot motion control for the spontaneous output of coherent periodic ***,the underlying CPG network exhibits good convergence performance only within a certain range of parameter spaces,and the coupling of oscillators affects the network output accuracy in complex topological ***,CPGs may diverge when parameters change drastically,and the divergence is irreversible,which is catastrophic for the control of robot ***,normalized asymmetric CPGs(NA-CPGs)that normalize the amplitude parameters of Hopf-based CPGs and add a constraint function and a frequency regulation mechanism are ***-CPGs can realize parameter decoupling,precise amplitude output,and stable and rapid convergence,as well as asymmetric output ***,it can effectively cope with large parameter changes to avoid network oscillations and *** optimize the parameters of the NA-CPG model,a reinforcement-learning-based online optimization method is further ***,a biomimetic robotic fish is illustrated to realize the whole optimization *** demonstrated that the designed NA-CPGs exhibit stable,secure,and accurate network outputs,and the proposed optimization method effectively improves the swimming speed and reduces the lateral swing of the multijoint robotic fish by 6.7%and 41.7%,*** proposed approach provides a significant improvement in CPG research and can be widely employed in the field of robot motion control.

关键词： Normalized asymmetric CPGs Rhythm generator Motion control Robotic fish

来源：评论

学校读者我要写书评

暂无评论

Development and Optimization of a WebGL-Based Mechanical Model Simulation Platform 4th

Development and Optimization of a WebGL-Based Mechanical Mod...

引用

4th International Conference on Mechanical Design and Simulation, MDS 2024

作者： Wang, Xintong Tian, Hao Fang, Jingzhe Zhang, Hualiang Zhang, Tao Software College Shenyang University of Technology Liaoning Shenyang China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China School of Electrical Engineering Shenyang University of Technology Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China

ISBN: (纸本)9789819778867

The need for mechanical model simulation platforms is growing as a result of the ongoing advancements in digital technology and the mechanical manufacturing sector. The application scope and efficacy of simulation platforms are severely limited by the issue of sluggish rendering performance, which frequently arises when obtaining high-quality rendering. When drawing high demand mechanical models, a lot of processing power is frequently needed, which makes real-time rendering speed unsatisfactory for practical purposes. In order to achieve real-time rendering and simulation of 3D robots, this experiment built and implemented a WebGL-based 3D simulation platform. Additionally, the simulation platform can be optimized by increasing frame rate and rendering speed without sacrificing rendering effect by building a mixed bounding box. © The Author(s) 2025.

关键词： Digital elevation model

来源：评论

学校读者我要写书评

暂无评论

Prior Knowledge Informed Neural Network for Subsurface Flow Prediction

Prior Knowledge Informed Neural Network for Subsurface Flow ...

引用

IEEE International Symposium on Industrial Electronics (ISIE)

作者： Haibo Cheng Shichao Li Peng Zeng State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China

ISBN: (数字)9798350394085

ISBN: (纸本)9798350394092

Data-driven deep learning has been widely applied to solve subsurface flow problems. However, it is difficult to achieve accurate prediction with pure data-driven methods, especially when there is only a small amount of valid data. Prior knowledge is pre-existent and comes from an independent source. The neural network can be informed by prior knowledge to improve algorithm performance even with limited and sparse data. In this study, prior knowledge informed neural network (PKINN) is proposed to predict subsurface flow. The prior knowledge, on the one hand, is embedded in the neural networks as integrated loss function to inform the training process of deep learning methods. On the other hand, it is used as part of input term of neural network to improve calculation accuracy. Subsurface flow models are built to verify the proposed PKINN model. The results show that the PKINN method can solve subsurface flow problems effectively.

关键词： Knowledge engineering Deep learning Training Industrial electronics Solid modeling Accuracy Neural networks

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：