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检索条件"任意字段=3rd International Conference on Informatics in Control, Automation and Robotics"

共 2682 条记录，以下是681-690 订阅

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Backstepping controller Applied to a Foldable Quadrotor for 3D Trajectory Tracking 17

Backstepping Controller Applied to a Foldable Quadrotor for ...

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17th international conference on informatics in control, automation and robotics (ICINCO)

作者： Derrouaoui, Saddam Hocine Bouzid, Yasser Guiatni, Mohamed Kada, Halfaoui Dib, Islam Moudjari, Noureddine Ecole Mil Polytech Complex Syst Control & Simulators Lab Algiers Algeria

ISBN: (纸本)9789897584428

This paper presents a novel design and architecture control of a foldable quadrotor. This design is based on a variable geometry that can be changed during the flight. It is able to modify the orientation of its arms independently, thanks to its special morphology. This quadrotor, exploits simple mechanisms i.e. rotating arms. We stress that the control of this category of robots is not obvious compared to the conventional ones. So, a detailed generic model and backstepping control that take into account the variation of the center of gravity and the inertia are presented. Simulation results are also provided in order to illustrate the performances of this controller.

关键词： Foldable Quadrotor Robot Design Rotating Arms Variable Geometry Adaptive Morphology Generic Modeling control Backstepping PID

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Design and Implementation of Adaptive NMPC in industrial applications: case study

Design and Implementation of Adaptive NMPC in industrial app...

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international Carpathian control conference (ICCC)

作者： Stepan Ozana Filip Krupa Jakub Nemcik Gergely Takacs Jakub Mozaryn Petr Beremlijski Abhaya Singh Aleksandra Kawala-Sterniuk Department of Cybernetics and Biomedical Engineering VSB-Technical University of Ostrava Ostrava Czech Republic Institute of Automation Measurement and Applied Informatics Slovak University of Technology in Bratislava Bratislava Slovak Republic Institute of Automatic Control and Robotics Warsaw University of Technology Warsaw Poland Department of Applied Mathematics VSB-Technical University of Ostrava Ostrava Czech Republic Department of engineering University of Sannio Sannio Italy Department of Electrical Power and Renewable Energy Opole University of Technology Opole Poland

This paper deals with the design and implementation of adaptive nonlinear predictive control (NMPC). The resulting control system is deployed on a softPLC embedded target in real-time via the REXYGEN control system. The paper describes functional prototype using softPLC hosting the NMPC algorithm applied for a nonlinear system consisting of three coupled tanks. The NMPC algorithm is solved via the receding horizon control method (RHC), formulated as a nonlinear programming problem (NLP) and numerically computed using the SOLNP solver. The adaptivity is provided by online identification via moving horizon estimation (MHE), keeping the model updated to avoid a model-plant mismatch. The methodology described in this paper can be easily transferred to a wider group of industrial nonlinear processes. Such created control unit can run in a standalone mode or can be connected to some exiting control system providing a necessary computational power and thus upgrading the quality of control significantly.

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Automatic Domain Extension and Optimization Based on Set-Theory 17th

Automatic Domain Extension and Optimization Based on Set-T...

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17th international conference on informatics in control, automation and robotics, ICINCO 2020

作者： Kast, Bernd Dietrich, Vincent Albrecht, Sebastian von Wichert, Georg Feiten, Wendelin Zhang, Jianwei Siemens AG Corporate Technology Otto-Hahn-Ring 6 Munich81739 Germany Faculty of Mathematics Informatics and Natural Sciences University of Hamburg Vogt-Kölln-Str. 30 Hamburg22527 Germany

ISBN: (纸本)9783030924416

Autonomous machines promise more flexibility and robustness changes in their environment compared to manually programmed solutions in industrial applications. However, the autonomous planning of actions involves discrete as well as continuous properties, which results in a np-hard planning problem. Especially for multiple machines and long planning horizons the design of domains requires a lot of fine tuning and thus manual effort. Modularization and reuse of existing domain knowledge with formalized models is one solution to this issue. However, the models of different projects tend to be misaligned, in particular when several parties contributed to the project, which deteriorates the performance. In this paper, we present two domain optimization and extension algorithms, which adapt the models to facilitate planning. The first algorithm handles inconsistent units, or even misaligned pieces of sub-information. It automatically generates conversions and allows to call operations with a wider range of input types. The second algorithm aligns models from different sources with varying modeling views. After this reformulation, we can compose models more efficiently to a larger domain. For both optimizations, we rely on the formal set-based models that we also use in our previously presented hierarchical planning algorithm. Our hierarchical approach allows an almost linear scalability with the length of the plan. However, it comes with non-optimality effects due to the imposed intermediate goals that depend on the quality of the model. The optimization algorithms of this paper allow to adapt and extend the model so that valid shortcuts reduce these suboptimalities. We conduct experiments on a task and motion assembly problem, demonstrating scalability for up to 62 parts and plans with over 1000 steps, which either result in discrete state or high-level position changes, with planning times of less than 15 min. Our experiments also include the successful plan execution o

关键词： Scalability

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Point, Segment, and Inspect: Leveraging Promptable Segmentation Models for Semi-Autonomous Aerial Inspection

Point, Segment, and Inspect: Leveraging Promptable Segmentat...

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IEEE international Workshop on Robot and Human Communication (ROMAN)

作者： Riccardo Franceschini Javier Rodriguez Marquez Matteo Fumagalli Julian Cayero Becerra Eurecat Centre Tecnològic de Catalunya Robotics and Automation Unit Cerdanyola del Vallès Barcelona Spain Department of Electrical Engineering Automation and Control Group Danish Technical University Lyngby Denmark

ISBN: (数字)9798350375022

ISBN: (纸本)9798350375039

Operating unmanned aerial vehicles (UAVs) for assets inspections poses distinct challenges encompassing the need to maintain a safe distance from the inspection area, ensure correct orientation towards the inspected surface, and achieve comprehensive coverage of the entire surface. Achieving these tasks is inherently complex and stressful. Therefore, a novel approach that seeks to enhance the piloting experience by harnessing the latest advancements in segmentation models, such as Segment Anything Model (SAM), is proposed. These models, thanks to their prompting capabilities, allow seamless communication between the operator and the UAV, opening up the possibility of defining intricate inspection regions through simple interactions. Within this approach, decision-making authority remains with the operator, while the UAV takes on the demanding task of segmenting the designated area and devising an appropriate traversal plan. Throughout this process, the operator’s situational awareness is heightened through visual cues overlaid on the camera stream and a 3D panel presenting information of the drone position and spatially sensed data. This teleoperation framework allows the operator to maintain continuous control of the ongoing operation through a simplified interface. The paper delineates both the system and the methodology employed, showcasing the effectiveness of integrating segmentation models into the decision-making workflow. The validity of the proposed framework is established through testing within a photorealistic UAV simulator along with real experiments in a controlled laboratory environment.

关键词： Visualization Three-dimensional displays Decision making Laboratories Inspection Traveling salesman problems Autonomous aerial vehicles Robot sensing systems Spatial databases Surface treatment

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A new structure of end-effector traction upper limb rehabilitation robot

A new structure of end-effector traction upper limb rehabili...

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2021 IEEE international conference on Real-Time Computing and robotics, RCAR 2021

作者： Li, Liaoyuan Han, Jianhai Li, Xiangpan Guo, Bingjing Xia, Pengpeng Du, Ganqin Henan University of Science and Technology Key Laboratory of Robotics and Intelligent Systems School of Mechanical and Electrical Engineering Luoyang471000 China First Affiliated Hospital of Henan University of Science and Technology Department of Neurology Luoyang471000 China

ISBN: (纸本)9781665436786

Among the rehabilitation therapies for patients with stroke or paralysis, robot-assisted rehabilitation is a research hotspot now. However, there are not many cases of clinical application, mainly because of the complex structure, single function, or high cost. This research proposes a new type of 3-DOF (degrees of freedom) upper limb rehabilitation robot in series structure of with an end-effector, which has 2 degrees of freedom in horizontal rotation and 1 degree of freedom in the vertical movement. It has a compact structure, saves space, is easy to be moved and can realize rehabilitation training in three-dimensional space. It is mainly used for rehabilitation training of the shoulder and elbow joints of the upper limbs. The first two rotary joints are driven by AC servo motors, and the prismatic joint is driven by a single-acting cylinder, which increases the passive compliance of the robot. In addition, a three-dimensional force sensor is added to expand the human-machine interaction channel and increase the active safety of the robot. Through the trajectory tracking and force control test of the robot, it is proved that the device can meet the demand of passive and active upper limb rehabilitation. © 2021 IEEE.

关键词： End effectors

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Image saliency detection via multi-feature and manifold-space ranking 2021

Image saliency detection via multi-feature and manifold-spac...

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3rd Asia Pacific Information Technology conference, APIT 2021

作者： Li, Xiaoli Zhao, Huaici Liu, Yunpeng 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 Key Laboratory of Opto-Electronic Information Processing Shenyang110016 China The Key Lab of Image Understanding and Computer Vision Shenyang110016 China Shenyang Jianzhu University Shenyang110168 China

ISBN: (纸本)9781450388108

In this paper, we propose an image saliency detection method by using multi-feature and manifold-space ranking. Basically, the proposed method extracts the color-histogram feature to obtain the fine information of the image, and the color-mean feature to obtain the coarse information respectively. To further improve the detection accuracy of the feature correlation between different image units, a manifold-space ranking method is used to calculate saliency values of image units to construct a saliency map on each feature-space. Specifically, we fuse the two saliency maps to obtain the final saliency map. Extensive experiments demonstrate that the proposed method not only outperforms the other methods, but also improves the accuracy and robustness of the saliency detection. © 2021 ACM.

关键词： Color

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Trends in Computer Networking Congestion control: A Bibliometric Analysis 3rd

Trends in Computer Networking Congestion Control: A Bibliome...

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3rd international conference on Advanced Research in Technologies, Information, Innovation and Sustainability, ARTIIS 2023

作者： Nketsiah, Richard Nana Agbehadji, Israel Edem Millham, Richard C. Iwarere, Samuel A. Freeman, Emmanuel ICT and Society Research Group Department of Information Technology Durban University of Technology Durban South Africa Honorary Research Associate Faculty of Accounting and Informatics Durban University of Technology P.O. Box 1334 Durban4000 South Africa Department of Chemical Engineering Faculty of Engineering Built Environment and Information Technology University of Pretoria Hatfield Pretoria0002 South Africa Faculty of Computing and Information Systems Ghana Communication Technology University PMB 100 Accra North Ghana

ISBN: (纸本)9783031488573

Computer networking congestion control is an important area of research. This study presents a bibliometric analysis of trends in computer networking congestion control research over the past decade. A total of 1,156 papers published in top-tier networking conferences and journals were analyzed using various bibliometric techniques. The results of the analysis show that the number of publications in this field has been steadily increasing over the years, with a significant rise in the number of publications related to machine learning-based congestion control techniques. The study identifies the most influential authors, institutions, and countries in this field. The analysis also identifies the most frequently cited papers, which provide valuable insights into the key concepts and developments in this field. This study provides a comprehensive overview of the trends in computer networking congestion control research and highlights the most promising research directions for future work. The outcome of the review highlights issues that are beneficial to reforming policy and informing network practitioners. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Computer networks

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Vector based control Routines for Swarms of Path Finding Robotic Devices 17

Vector based Control Routines for Swarms of Path Finding Rob...

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17th international conference on informatics in control, automation and robotics (ICINCO)

作者： Chibaya, Colin Sol Plaatje Univ Chapel Rd Kimberley South Africa

ISBN: (纸本)9789897584428

Swarm intelligence systems where robotic devices encoded with primitive actions executed at individual levels in order to cause swarm level emergent behaviour are appealing to the fields of nanotechnology and bioinformatics. Interaction between robotic devices allow improved swarm level properties with features more than the sum of the contributions of the individual robotic devices that form the swarm. However, it is challenging to pinpoint particular primitive actions which drive robotic devices towards deliberately engineered emergent behaviour. We propose an XSet model inspired by the behaviours of message passing agents. The proposed XSet model supports direct device to device interactions in which implicit communication spaces arise. In this context, an XSet puts together primitive actions, parameters, and meta information which stipulates when primitive actions are useful to robotic devices. We assess path finding and path following abilities of message passing robotic devices and compared the measures thereof to the relative performances of the stigmergic counterparts. Better message passing performances are observed when time in simulation is sufficiently long, when the population of robotic devices in the swarm is high. Besides giving a new swarm control model, message passing XSets bring us closer to more generalized swarm control rules.

关键词： XSet control Routines Message Passing Robotic Devices Emergent Behaviour

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Evaluation of Lyapunov Function Candidates through Averaging Iterations 17

Evaluation of Lyapunov Function Candidates through Averaging...

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17th international conference on informatics in control, automation and robotics (ICINCO)

作者： Argaez, Carlos Giesl, Peter Hafstein, Sigurdur Univ Iceland Sci Inst Dunhagi 3 IS-107 Reykjavik Iceland Univ Sussex Dept Math Falmer BN1 9QH England

ISBN: (纸本)9789897584428

A complete Lyapunov function determines the behaviour of a dynamical system. In particular, it splits the phase space into the chain-recurrent set, where solutions show (almost) repetitive behaviour, and the part exhibiting gradient-like flow where the dynamics are transient. Moreover, it reveals the stability of sets and basins of attraction through its sublevel sets. In this paper, we combine two previous methods to compute complete Lyapunov functions: we employ quadratic optimization with equality and inequality constraints to compute a complete Lyapunov function candidate and we evaluate its quality by using a method that improves approximations of complete Lyapunov function candidates through iterations.

关键词： Complete Lyapunov Functions Chain-recurrent Set Numerical Methods Dynamical Systems Iterative Methods

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Bearing Fault Diagnosis Integrated Model Based on Hierarchical Fuzzy Entropy, Convolutional Neural Network and Long Short - Term Memory 3

Bearing Fault Diagnosis Integrated Model Based on Hierarchic...

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3rd international conference on Sensing, Measurement and Data Analytics in the Era of Artificial Intelligence, ICSMD 2022

作者： Mwelinde, Avitus Titus Han, Zhenyu Jin, Hongyu Abayo, Timothy Fu, Hongya School of Mechatronics Engineering Harbin Institute of Technology Harbin China School of Informatics and Information Technology Sokoine University of Agriculture Morogoro Tanzania United Republic of

ISBN: (纸本)9781665492812

Bearings are the most critical components in most rotating machineries, whose stability and reliable working condition plays a vital role in ensuring the reliability of the whole system. Hence, it becomes crucial to monitor its performance condition in order to anticipate failures before their occurrence. In recent years, the signal processing techniques and deep learning techniques have been extensively researched and have achieved a remarkable success in bearing fault diagnosis applications. However, these methods have been used in a singly form and most machine learning techniques require a huge amount of data for accurate fault classification. For an efficient and accurate bearing fault classification, we propose an integrated model based on Hierarchical Fuzzy Entropy (HFE), Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM). The model basically consists of two parts;Feature extraction and Fault classification. In addition, an Intensity Discriminator (ID) is embedded in the CNN to effectively extract crucial features that reflect the true condition of the bearing, to enhance model computational efficiency and classification accuracy. The experimental results demonstrated the effectiveness the proposed model by achieving better classification accuracy with high computational efficiency, strong generalization ability and limited training data. © 2022 IEEE.

关键词： bearings convolutional neural network fault classification feature extraction hierarchical fuzzy entropy intensity discriminator component long short-term memory

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