检索结果-内蒙古大学图书馆

IEEE International Conference on Robotics and Biomimetics

作者： Shujuan Liu Shaowei Cui Chaofan Zhang Yinghao Cai Shuo Wang University of Science and Technology Beijing State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China Institute of Automation Chinese Academy of Sciences Beijing China Center for Excellence in Brain Science Intelligence Technology Chinese Academy of Sciences Shanghai China

ISBN: (纸本)9781665481106

Visuotactile sensing technology is becoming more popular in tactile sensing, but the effectiveness of the existing marker detection/localization methods remains to be further explored. Instead of contour-based blob detection, this paper presents a learning-based marker localization network for GelStereo visuotactile sensing called Marknet. Specifically, the Marknet presents a grid regression architecture to incorporate the distribution of the GelStereo markers. Furthermore, a marker rationality evaluator (MRE) is modelled to screen suitable prediction results. The experimental results show that the Marknet combined with MRE achieves 93.90% precision for irregular markers in contact areas, which outperforms the traditional contour-based blob detection method by a large margin of 42.32%. Meanwhile, the proposed learning-based marker localization method can achieve better realtime performance beyond the blob detection interface provided by the OpenCV library through GPU acceleration, which we believe will lead to considerable perceptual sensitivity gains in various robotic manipulation tasks.

关键词： Location awareness Sensitivity Object detection Network architecture Predictive models Robot sensing systems Real-time systems

来源：评论

学校读者我要写书评

暂无评论

A Novel Two-Stream Model for Human Motor Characteristics Learning

A Novel Two-Stream Model for Human Motor Characteristics Lea...

引用

IEEE International Conference on Robotics and Biomimetics

作者： Tian-Yu Xiang Xiao-Hu Zhou Xiao-Liang Xie Shi-Qi Liu Hong-Jun Yang Zhen-Qiu Feng Jian-Long Hao Zeng-Guang Hou The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China The School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China The school of Information Shanxi University of Finance and Economics Taiyuan China The CAS Center for Excellence in Brain Science and Intelligence Technology Beijing China The Joint Laboratory of Intelligence Science and Technology Institute of Systems Engineering Macau University of Science and Technology Taipa Macau

ISBN: (纸本)9781665481106

Electroencephalogram (EEG) is one of the most pop-ular sources for learning human motor characteristics. However, most current methods only consider its temporal features and overlook spatial information. This paper proposes a novel two-stream model based on spatial and temporal features to learn human motor characteristics from EEG signals. The spatial stream is analyzed by graph neural networks (GNN) to extract the relationship among different channels. Adjacent matrices can be learned through the training process, unlike pre-defined ones used in other GNN-based EEG analysis methods. The temporal stream is processed with mixed convolution structures, which consist ID convolution, depthwise convolution, and separable convolution. The features of two streams are fused with fully-connected neural networks for human motor characteristics learning. Experimental results show the proposed model can achieve the accuracy of 0.684/0.709 (four classes motor imagery) in subject-independent/dependent schemes, demonstrating the promising for it used in brain computer interface (BCI) scenarios.

关键词： Training Convolution Computational modeling Biological system modeling Streaming media Brain modeling Electroencephalography

来源：评论

学校读者我要写书评

暂无评论

Simulation and Field Testing of Multiple Vehicles Collision Avoidance Algorithms

引用

IEEE/CAA Journal of Automatica Sinica 2020年第4期7卷 1045-1063页

作者： Chaoyue Zu Chao Yang Jian Wang Wenbin Gao Dongpu Cao Fei-Yue Wang the College of Computer Science and Technology Jilin UniversityChangchun 130012China Jiangsu XCMG Construction Machinery Research Institute Ltd. Xuzhou 221004China the College of Computer Science and Technology Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of EducationJilin UniversityChangchun 130012 Chongqing Xibu Automobile Proving Ground Management Co.Ltd. Chongqing 404100China the State Grid JIBEI Electric Power Company Limited Management Training Center China the Advanced Vehicle Engineering Center Cranfield UniversityCranfield MK430ALUK the State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China

A global planning algorithm for intelligent vehicles is designed based on the A* algorithm, which provides intelligent vehicles with a global path towards their destinations. A distributed real-time multiple vehicle collision avoidance(MVCA)algorithm is proposed by extending the reciprocal n-body collision avoidance method. MVCA enables the intelligent vehicles to choose their destinations and control inputs independently,without needing to negotiate with each other or with the coordinator. Compared to the centralized trajectory-planning algorithm, MVCA reduces computation costs and greatly improves the robustness of the system. Because the destination of each intelligent vehicle can be regarded as private, which can be protected by MVCA, at the same time MVCA can provide a real-time trajectory planning for intelligent vehicles. Therefore,MVCA can better improve the safety of intelligent vehicles. The simulation was conducted in MATLAB, including crossroads scene simulation and circular exchange position simulation. The results show that MVCA behaves safely and reliably. The effects of latency and packet loss on MVCA are also statistically investigated through theoretically formulating broadcasting process based on one-dimensional Markov chain. The results uncover that the tolerant delay should not exceed the half of deciding cycle of trajectory planning, and shortening the sending interval could alleviate the negative effects caused by the packet loss to an extent. The cases of short delay(< 100100 ms) and low packet loss(< 5%) can bring little influence to those trajectory planning algorithms that only depend on V2 V to sense the context, but the unpredictable collision may occur if the delay and packet loss are further worsened. The MVCA was also tested by a real intelligent vehicle, the test results prove the operability of MVCA.

关键词： Collision avoidance intelligent vehicles intervehicle communication simulation testing trajectory planning

来源：评论

学校读者我要写书评

暂无评论

Lightweight Double Attention-Fused Networks for Intraoperative Stent Segmentation 23rd

Lightweight Double Attention-Fused Networks for Intraoperati...

引用

23rd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2020

作者： Zhou, Yan-Jie Xie, Xiao-Liang Hou, Zeng-Guang Zhou, Xiao-Hu Bian, Gui-Bin Liu, Shi-Qi State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China CAS Center for Excellence in Brain Science and Intelligence Technology Beijing100190 China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing100049 China

ISBN: (纸本)9783030597245

In endovascular interventional therapy, the fusion of preoperative data with intraoperative X-ray fluoroscopy has demonstrated the potential to reduce radiation dose, contrast agent and processing time. Real-time intraoperative stent segmentation is an important pre-requisite for accurate fusion. Nevertheless, this task often comes with the challenge of the thin stent wires with low contrast in noisy X-ray fluoroscopy. In this paper, a novel and efficient network, termed Lightweight Double Attention-fused Network (LDA-Net), is proposed for end-to-end stent segmentation in intraoperative X-ray fluoroscopy. The proposed LDA-Net consists of three major components, namely feature attention module, relevance attention module and pre-trained MobileNetV2 encoder. Besides, a hybrid loss function of both reinforced focal loss and dice loss is designed to better address the issues of class imbalance and misclassified examples. Quantitative and qualitative evaluations on 175 intraoperative X-ray sequences demonstrate that the proposed LDA-Net significantly outperforms simpler baselines as well as the best previously-published result for this task, achieving the state-of-the-art performance. © 2020, Springer Nature Switzerland AG.

关键词： Stents

来源：评论

学校读者我要写书评

暂无评论

Multi-objective IGDT-based scheduling of low-carbon multi-energy microgrids integrated with hydrogen refueling stations and electric vehicle parking lots

引用

Sustainable Cities and Society 2021年 74卷

作者： Mansour-Saatloo, Amin Ebadi, Ramin Mirzaei, Mohammad Amin Zare, Kazem Mohammadi-Ivatloo, Behnam Marzband, Mousa Anvari-Moghaddam, Amjad Faculty of Electrical and Computer Engineering University of Tabriz Tabriz Iran Department of Electrical Engineering Sahand University of Technology Tabriz Iran Northumbria University Electrical Power and Control Systems Research Group Ellison PlaceNewcastle upon TyneNE1 8ST United Kingdom Aalborg University Aalborg9220 Denmark Center of Research Excellence in Renewable Energy and Power Systems King Abdulaziz University Jeddah Saudi Arabia

There is little room for doubt that distributed generation systems including renewable energy, microgrids (MGs), combined heat and power (CHP) units and storage systems have been of particular importance in sustaining low-carbon and cost-effective operations due to the tremendous increase in greenhouse gas emissions in recent years. Additionally, hydrogen-based power technologies have earned a great deal of publicity that hydrogen can serve as a zero-emission fuel for electrical power and thermal energy production. In this regard, the current paper proposes an optimal energy management strategy for a combined hydrogen, heat, and power MG (CHHP-MG) with hydrogen fueling stations (HFSs) for hydrogen vehicles (HVs), electric vehicle parking lots (EVPLs) and fuel cell micro-CHP (FC-MCHP) units to meet power and heat requirements. In order to reduce the regular operating expense, the presented CHHP-MG could also communicate with both electricity and hydrogen markets. In addition, to compensate for the associated heat and hydrogen requirements, power-to-X technologies such as the power to heat (P2HT) and power to hydrogen (P2H) are integrated. In order to improve flexibility and build a low carbon MG, multi-energy storage (MES) system along with heat and power demand response (HPDR) programs will be taken into consideration. As the uncertainties associated with the predicted wind and photovoltaic power have a major impact on the energy management of the CHHP-MG, a multi-objective information gap decision theory (IGDT)-based robust approach is applied as an effective non-probabilistic modeling technique for handling such uncertainties. The empirical results show that the proposed model can efficiently handle the uncertainties and reduce the overall operation cost by 76.35%. © 2021 Elsevier Ltd

关键词： Energy management

来源：评论

学校读者我要写书评

暂无评论

Hierarchical Learning from Demonstrations for Long-Horizon Tasks

Hierarchical Learning from Demonstrations for Long-Horizon T...

引用

IEEE International Conference on Robotics and Automation (ICRA)

作者： Boyao Li Jiayi Li Tao Lu Yinghao Cai Shuo Wang China Academy of Launch Vehicle Technology Beijing China State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Center for Excellence in Brain Science and Intelligence Technology Chinese Academy of Sciences Shanghai China

Although reinforcement learning (RL) has achieved great success in robotic manipulation skills learning, it is still challenging for long-horizon tasks. Combining RL with demonstrations is an effective solution. In this paper, we propose a novel hierarchical learning from demonstrations method for long-horizon tasks, which leverages (i) object-centered segmentation of demonstrations to automatically segment the teaching trajectories into episodes. (ii) a bi-level hierarchical imitation learning method with a parallel training mechanism to train the two-level policies simultaneously. Experimental results on three challenging long-horizon tasks with sparse rewards show that our proposed method significantly outperforms state-of-art approaches in terms of both sample-efficiency and success rate. Moreover, our method is the only one which achieves satisfactory performance in tasks of multi-object stack and multi-object push&stack.

关键词： Deep learning Training Learning systems Automation Conferences Reinforcement learning Trajectory

来源：评论

学校读者我要写书评

暂无评论

Internet of Mind with General Intelligent Dispatch in Electrical Industrial: The Concept, Framework, Technology, and Future

Internet of Mind with General Intelligent Dispatch in Electr...

引用

Youth Academic Annual Conference of Chinese Association of Automation (YAC)

作者： Tianlu Gao Xiaoyan Gong Shiqian Ma Weichen Wang Xiaojing Yang Jian Wang The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Science Beijing China Power Dispatching and Control center State Grid Tianjin Electric Power Company Tianjin China

ISBN: (数字)9781728176840

ISBN: (纸本)9781728176857

This paper proposes the concept of general intelligent dispatch, which is a novel framework of electrical power dispatch based on modern artificial intelligence (AI). The general intelligent dispatch system is based on knowledge automation, parallel system, ACP method, and fully integrated with cutting-edge technologies such as parallel deep learning, parallel dynamics programming. The general intelligent dispatch system is devised to be a comprehensive framework that can support the applications of various modern AI technologies in electrical power dispatch. General intelligent dispatch can accommodate the rapid development of the future smart grid, especially the extensive implementation of distributed energy resources and renewable energy. General intelligent dispatch also provides the practical technical path and framework for the future smart power dispatch services to achieve a higher level of automation and intelligence. Based on the general intelligent dispatch concept, this paper addresses power grid situational awareness, which provides an example for the applications of general intelligent dispatch.

关键词： Automation Optimal scheduling Real-time systems Dispatching Smart grids Artificial intelligence Business

来源：评论

学校读者我要写书评

暂无评论

Spatial confinement: A green pathway to promote the oxidation processes for organic pollutants removal from water

引用

Water research 2023年 233卷 119719页

作者： Huan Yi Eydhah Almatrafi Dengsheng Ma Xiuqing Huo Lei Qin Ling Li Xuerong Zhou Chengyun Zhou Guangming Zeng Cui Lai College of Environmental Science and Engineering Hunan University and Key Laboratory of Environmental Biology and Pollution Control (Hunan University) Ministry of Education Changsha 410082 P.R. China Center of Research Excellence in Renewable Energy and Power Systems Center of Excellence in Desalination Technology Department of Mechanical Engineering Faculty of Engineering-Rabigh King Abdulaziz University Jeddah 21589 Saudi Arabia. College of Environmental Science and Engineering Hunan University and Key Laboratory of Environmental Biology and Pollution Control (Hunan University) Ministry of Education Changsha 410082 P.R. China. Center of Research Excellence in Renewable Energy and Power Systems Center of Excellence in Desalination Technology Department of Mechanical Engineering Faculty of Engineering-Rabigh King Abdulaziz University Jeddah 21589 Saudi Arabia. Electronic address: zgming@***. Center of Research Excellence in Renewable Energy and Power Systems Center of Excellence in Desalination Technology Department of Mechanical Engineering Faculty of Engineering-Rabigh King Abdulaziz University Jeddah 21589 Saudi Arabia. Electronic address: laicui@***.

Organic pollutants removal from water is pressing owing to the great demand for clean water. Oxidation processes (OPs) are the commonly used method. However, the efficiency of most OPs is limited owing to the poor mass transfer process. Spatial confinement is a burgeoning way to solve this limitation by use of nanoreactor. Spatial confinement in OPs would (i) alter the transport characteristics of protons and charges; (ii) bring about molecular orientation and rearrangement; (iii) cause the dynamic redistribution of active sites in catalyst and reduce the entropic barrier that is high in unconfined space. So far, spatial confinement has been utilized for various OPs, such as Fenton, persulfate, and photocatalytic oxidation. A comprehensive summary and discussion on the fundamental mechanisms of spatial confinement mediated OPs is needed. Herein, the application, performance and mechanisms of spatial confinement mediated OPs are overviewed firstly. Subsequently, the features of spatial confinement and their effects on OPs are discussed in detail. Furthermore, environmental influences (including environmental pH, organic matter and inorganic ions) are studied with analyzing their intrinsic connection with the features of spatial confinement in OPs. Lastly, challenges and future development direction of spatial confinement mediated OPs are proposed.

关键词： Local enrichment of substances Mass transfer Organic polluted water Oxidation process Spatial confinement

来源：评论

学校读者我要写书评

暂无评论

The Application of Artificial Intelligence in Energy Internet

The Application of Artificial Intelligence in Energy Interne...

引用

Youth Academic Annual Conference of Chinese Association of Automation (YAC)

作者： Zhigang Huang Tianlu Gao Xiaoyan Gong Qian Li Wenzhong Gao Power Dispatching and Control Center State Grid Tianjin Electric Power Company Tianjin China The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Science Beijing China

ISBN: (数字)9781728176840

ISBN: (纸本)9781728176857

The energy internet is a cyber-physical system (CPS) to connect directly and indirectly the devices of information, communication, control, and protection to effectively generate, transmit, use, and store various energy by merging new technologies such as artificial intelligence (AI), cloud computing, and blockchain, etc. Recently, AI technology has become increasingly popular in many research and industrial fields because it can perform tasks well. However, applying AI technologies to energy internet is relatively less. Therefore, in this paper, the potential applications of AI technologies in the energy internet will be reviewed and discussed. In section II and section III, the operating and monitoring of power systems are the main parts to discuss. Firstly, applying AI technologies to the operation of control, optimization, and decision-making in power systems will be detailed in section II from three aspects such as existing problems, potential demands, and valuable improvement. Secondly, in section III, detecting faults and analyzing stability by energy internet monitoring is mainly discussed. Finally, in section IV, it shows an example using the neural network to analyze the power flow of a standard IEEE 39 nodes power system compared with traditional Newton-Raphson method.

关键词： Decision making power system stability Stability analysis power grids Artificial intelligence Monitoring Optimization

来源：评论

学校读者我要写书评

暂无评论

Real-Time Marker Localization Learning for GelStereo Tactile Sensing

arXiv

引用

arXiv 2022年

作者： Liu, Shujuan Cui, Shaowei Zhang, Chaofan Cai, Yinghao Wang, Shuo The University of Science and Technology Beijing China The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China The School of Artificial Intelligence University of Chinese Academy of Sciences Beijing100049 China Institute of Automation Chinese Academy of Sciences Beijing100190 China The Center for Excellence in Brain Science and Intelligence Technology Chinese Academy of Sciences Shanghai200031 China

Visuotactile sensing technology is becoming more popular in tactile sensing, but the effectiveness of the existing marker detection/localization methods remains to be further explored. Instead of contour-based blob detection, this paper presents a learning-based marker localization network for GelStereo visuotactile sensing called Marknet. Specifically, the Marknet presents a grid regression architecture to incorporate the distribution of the GelStereo markers. Furthermore, a marker rationality evaluator (MRE) is modelled to screen suitable prediction results. The experimental results show that the Marknet combined with MRE achieves 93.90% precision for irregular markers in contact areas, which outperforms the traditional contour-based blob detection method by a large margin of 42.32%. Meanwhile, the proposed learning-based marker localization method can achieve better real-time performance beyond the blob detection interface provided by the OpenCV library through GPU acceleration, which we believe will lead to considerable perceptual sensitivity gains in various robotic manipulation tasks. Copyright © 2022, The Authors. All rights reserved.

关键词： Machine learning

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：