检索结果-内蒙古大学图书馆

第35届中国控制与决策会议

作者： Tao Zhang Xintong Wang Yun Teng Jingzhe Fang Yiqiang Zhang Xiyou Chen School of Electrical Engineering Dalian University of Technology Shenyang Institute of Automation Chinese Academy of Sciences Key Laboratory of Networked Control Systems Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences School of Electrical Engineering Shenyang University of Technology

As science and technology have advanced,an increasing number of people are focusing their study on 3 D robot *** 3 D quick simulation of the mechanical arm can be achieved using 3 D modeling software and *** the third-party WebGL library *** to construct the simulation scenario,then interact with and render the 3 D scene and 3 D robot model directly on the Web,which is easier and faster than downloading *** essay briefly explains the benefits and applicability of *** in the creation of 3 D virtual simulations,then goes on to discuss the quick implementation process of 3 D robot simulations before summarizing the building technique.

关键词： webgl three.js 3D simulation robot

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Research on intrusion detection of industrial control system based on improved QPSO-SVM

Research on intrusion detection of industrial control system...

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2022 International Conference on Electronic Information Technology, EIT 2022

作者： Yu, Yajie Liu, Xianda Wei, Weixuan Chen, Hengfei 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 University of Chinese Academy of Sciences Beijing100049 China College of Information Engineering Shenyang University of Chemical Technology Shenyang110142 China

ISBN: (纸本)9781510655096

Intrusion detection technology can effectively evaluate the security state of the system. However, the accuracy of traditional intrusion detection methods still needs to be improved. Therefore, this paper proposed a SVM model based on improved QPSO. QPSO is used to optimize the hyperparameters of SVM to improve its accuracy. In addition, the shrinkage expansion coefficient in QPSO is improved to make QPSO adaptive. Experiment shows that the proposed algorithm has good performance. © 2022 SPIE. All rights reserved.

关键词： Intrusion detection

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Multi-view Self-supervised Object Segmentation

Multi-view Self-supervised Object Segmentation

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IEEE International Conference on robotics and Biomimetics

作者： Wenxuan Ma Liming Zheng Yinghao Cai Tao Lu Shuo Wang State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences Beijing China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China Centre for Artificial Intelligence and Robotics (CAIR) the Hong Kong Institute of Science & Innovation Chinese Academy of Sciences (HKISI-CAS)

Robots often operate in open-world environments, where the capability to generalize to new scenarios is crucial for robotic applications such as navigation and manipulation. In this paper, we propose a novel multi-view self-supervised framework (MVSS) to adapt off-the-shelf segmentation methods in a self-supervised manner by leveraging multi-view consistency. Pixel-level and object-level correspondences are established through unsupervised camera pose estimation and cross-frame object association to learn feature embeddings that the same object are close to each other and embeddings from different objects are separated. Experimental results show that it only needs to observe the RGB-D sequence once without any annotation, our proposed method is able to adapt existing methods in new scenarios to achieve performance close to that of supervised segmentation methods.

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Development of a Miniaturized Bedside Robotic Wrist with Multifunctional Movement Capabilities: An Analysis Based on a Simulation Environment

Development of a Miniaturized Bedside Robotic Wrist with Mul...

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Digital Twins and Parallel Intelligence (DTPI), IEEE International Conference on

作者： Pengcheng Zhang Zhaokun Deng Xilong Hou Shuangyi Wang State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences Beijing China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China Centre for Artificial Intelligence and Robotics Hong Kong Institute of Science & Innovation Chinese Academy of Sciences Hong Kong China

Bedside robots equipped with medical devices can be effective in assisting physicians to perform specific medical tasks on mobile medical vehicles via remote operation. However, the major challenges are to make the robot small and dexterous enough to meet the clinical requirements and fit into the small space of the mobile medical vehicle. In this paper, we propose a miniaturized bedside robotic wrist based on a 6-RSU parallel mechanism with multifunctional motion capabilities. The robotic wrist can be equipped with various medical instruments, including but not limited to ultrasound probes, biopsy needles and endoscopes. To meet different clinical needs, the motion mode of the robotic wrist can be switched between decoupled and remote center of motion. To verify the effectiveness of the design, the kinematic model of the robotic wrist for two motion modes was established and different simulation studies were performed. The experimental results show that the robotic wrist has a favorable working performance to be deployed onto mobile medical vehicles, demonstrating its promising application prospects.

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A Parallel and Asynchronous Blob Shape Descriptor Implemented in CMOS Technology

A Parallel and Asynchronous Blob Shape Descriptor Implemente...

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International Conference on Microelectronics, MIEL

作者： P. Bogacki M. Długosz T. Talaśka R. Długosz Aptiv Services Poland Kraków Poland Institute of Telecommunications Faculty of Computer Science Electronics and Telecommunications AGH University of Science and Technology Kraków Poland Faculty of Control Robotics and Electrical Engineering Institute of Automation and Robotics Division of Signal Processing and Electronic Systems Poznan University of Technology Poznan Poland Faculty of Telecommunication Computer Science and Electrical Engineering Bydgoszcz University of Science and Technology Bydgoszcz Poland

The paper presents a family of novel light blob shape descriptors for use in selected active safety algorithms used in Advanced Driver Assistance systems (ADAS). One of the motivations was to obtain a descriptor that would ensure low computational complexity. This makes it easy to implement both in software and hardware. One assumption is that the location of the center of a given light spot is approximately known. The principle of its operation is then to count white pixels in selected directions, starting from this central point. A key issue here is an efficient way of determining indexes of particular pixels belonging to the image patch, as well as the location of points representing places where the white area turns into black. In the case of a hardware implementation, this can be done using a parallel circuit operating in asynchronous mode, without the need for a control clock.

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Modeling and Control of A Bird-like Flapping Wing Aerial Vehicle Driven by Servos

Modeling and Control of A Bird-like Flapping Wing Aerial Veh...

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第34届中国控制与决策会议

作者： Shuangshuang Yu Qiang Lu Lin Fu Botao Zhang Sergey A.Chepinskiy Anton A.Zhilenkov HDU-ITMO Joint Institute Hangzhou Dianzi University School of Automation Hangzhou Dianzi University Faculty of Control Systems and Robotics ITMO University Institute of Hydrodynamics and Control Processes Saint-Petersburg State Marine Technical University

In this paper,dynamics modeling and control scheme of a flapping wing aerial vehicle driven by three servos are *** to the quasi-steady state theorem and the characteristics of flexible wings flapping movement,a simplified aerodynamic modeling scheme is proposed such that the body aerodynamic force and the flapping force of the flapping wing aerial vehicle are calculated and the relationship between its own attitude and aerodynamic force is ***,the Lagrangian position and attitude dynamics model are established based on the aerodynamic ***,in order to solve the problem of low modeling accuracy and strong disturbance in the flight process of flapping wing aerial vehicle that cannot keep stationary status,a cascaded structural sliding mode control method and the pathtracking scheme are ***,the flight control system is simulated in MATLAB,which illustrates that the sliding mode control method has good robustness.

关键词： Flapping wing aerial vehicle aerodynamic model sliding mode control path-tracking scheme

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SceneX: Procedural Controllable Large-scale Scene Generation 39

SceneX: Procedural Controllable Large-scale Scene Generation

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39th Annual AAAI Conference on Artificial Intelligence, AAAI 2025

作者： Zhou, Mengqi Wang, Yuxi Hou, Jun Zhang, Shougao Li, Yiwei Luo, Chuanchen Peng, Junran Zhang, Zhaoxiang University of Chinese Academy of Sciences China Institute of Automation Chinese Academy of Sciences China State Key Laboratory of Multimodal Artificial Intelligence Systems China New Laboratory of Pattern Recognition China Centre for Artificial Intelligence and Robotics Malaysia China University of Geosciences Beijing China Shandong University China University of Science and Technology Beijing China

ISBN: (纸本)157735897X

Developing comprehensive explicit world models is crucial for understanding and simulating real-world scenarios. Recently, Procedural Controllable Generation (PCG) has gained significant attention in large-scale scene generation by enabling the creation of scalable, high-quality assets. However, PCG faces challenges such as limited modular diversity, high expertise requirements, and challenges in managing the diverse elements and structures in complex scenes. In this paper, we introduce a large-scale scene generation framework, SceneX, which can automatically produce high-quality procedural models according to designers' textual descriptions. Specifically, the proposed method comprises two components, PCGHub and PCGPlanner. The former encompasses an extensive collection of accessible procedural assets and thousands of hand-craft API documents to perform as a standard protocol for PCG controller. The latter aims to generate executable actions for Blender to produce controllable and precise 3D assets guided by the user's instructions. Extensive experiments demonstrated the capability of our method in controllable large-scale scene generation, including nature scenes and unbounded cities, as well as scene editing such as asset placement and season translation. Copyright © 2025, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

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Deep Learning-Based Prediction of Subsurface Oil Reservoir Pressure Using Spatio-Temporal Data

Deep Learning-Based Prediction of Subsurface Oil Reservoir P...

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Annual Conference of Industrial Electronics Society

作者： Haibo Cheng Yunpeng He Peng Zeng Shichao Li Valeriy Vyatkin 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 University of Chinese Academy of Sciences Beijing China Department of Computer Science Electrical and Space Engineering Luleå University of Technology Luleå Sweden Department of Electrical Engineering and Automation Aalto University Helsinki Finland

Prediction of subsurface oil reservoir pressure are critical to hydrocarbon production. However, the accurate pressure estimation faces great challenges due to the complexity and uncertainty of reservoir. The underground seepage flow and petrophysical parameters (permeability and porosity) are important but difficult to measure in oilfield. Deep learning methods have been successfully used in reservoir engineering and oil & gas production process. In this study, the effective but inaccessible subsurface seepage fields are not used, only the spatial coordinates and temporal information are selected as model input to predict reservoir pressure. A stacked GRU-based deep learning model is proposed to map the relationship between spatio-temporal data and reservoir pressure. The proposed deep learning method is verified by using a three-dimensional reservoir model, and compared with commonly-used methods. The results show that the stacked GRU model has a better performance and higher accuracy than other deep learning or machine learning methods in pressure prediction.

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自主水下直升机——海洋探测的新平台

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Engineering 2023年第6期25卷 21-27页

作者：周晶黄豪彩黄善和司玉林石凯全向前郭春雷陈振纬王智鲲王英强王章霖蔡成业胡若愚荣振威何佳钟刘鸣陈鹰 Intelligent Ocean Technology Center Zhejiang UniversityZhoushan 316021China College of Electrical Engineering Zhejiang UniversityHangzhou 310027China Ocean College Zhejiang UniversityZhoushan 316021China State Key Laboratory of Fluid Power&Mechatronic Systems Zhejiang UniversityHangzhou 310027China State Key Laboratory of Robotics Shenyang Institute of AutomationChinese Academy of SciencesShenyang 110169China Institute of Deep-Sea Science and Engineering Chinese Academy of SciencesSanya 572000China

The demand for ocean exploration down to the deep seafloor,for instance,ocean resource exploration and ocean observations,has promoted innovations in underwater *** unmanned vehicles are urgently required to be deployed and operate on the *** most underwater vehicles are unable to operate on the seafloor and even have difficulty reaching there,we developed a seafloor-resident autonomous underwater helicopter(AUH).This paper introduces the new idea and design of AUHs and discusses the pros and cons of AUHs in comparison with other underwater ***,we verify the importance of developing new facilities to enable mankind to easily operate close to the seafloor.

关键词：海洋探测 ocean underwater

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Enhancing Precision Agriculture Through Human-in-the-Loop Planning and Control

Enhancing Precision Agriculture Through Human-in-the-Loop Pl...

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IEEE International Conference on automation Science and Engineering (CASE)

作者： Shankar A. Deka Sujet Phodapol Andreu Matoses Gimenez Victor Nan Fernandez-Ayala Rufus Wong Pian Yu Xiao Tan Dimos V. Dimarogonas Department of Electrical Engineering and Automation School of Electrical Engineering Aalto University Espoo Finland Division of Decision and Control Systems School of EECS Royal Institute of Technology (KTH) Stockholm Sweden Department of Cognitive Robotics Faculty of Mechanical Engineering TU Delft Delft Netherlands Department of Computer Science University of Oxford Oxford UK

ISBN: (数字)9798350358513

ISBN: (纸本)9798350358520

In this paper, we introduce a ROS based framework designed for the planning and control of robotic systems within the context of precision agriculture, with an emphasis on human-in-the-loop capabilities. Utilizing Linear Temporal Logic to articulate complex task specifications, our algorithm creates high-level robotic plans that are not only correct by design but also adaptable in real time by human operators. This dual-focus approach ensures that while humans have the flexibility to modify the high-level plan on-the-fly or even take over low-level control of the robots, the system inherently safeguards against any human actions that could potentially breach the predefined task specifications. We demonstrate our algorithm within the dynamic and challenging environment of a real vineyard, where the collaboration between human workers and robots is critical for tasks such as harvesting and pruning, and show the practical applicability and robustness of our software. This work marks a pioneering application of formal methods to complex, real-world agricultural environments.

关键词： Precision agriculture Heuristic algorithms Software algorithms Robustness Human in the loop Software Real-time systems Planning Robots Multi-agent systems

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