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2024 International Conference on Ocean Studies, ICOS 2024

作者： Gubankov, Anton Gornostaev, Igor Institute of Automation and Control Processes FEB RAS M.D. Ageev Institute of Marine Technology Problems Admiral G.I. Nevelskoy Maritime State University Robotics Laboratory Laboratory of Intelligent Information Systems for Marine Robots Laboratory of Marine Unmanned Aviation and Marine Aviation Systems Vladivostok Russia Institute of Automation and Control Processes FEB RAS M.D. Ageev Institute of Marine Technology Problems Admiral G.I. Nevelskoy Maritime State University Robotics Laboratory Laboratory of Robotic Systems Laboratory of Marine Unmanned Aviation and Marine Aviation Systems Vladivostok Russia

ISBN: (纸本)9798331532307

The article presents the results of the development of a method for the automatic formation of reference speeds for autonomous unmanned aerial vehicles of multirotor type, performing specified missions (such as monitoring of the sea and coastal territory in order to track populations of rare and endangered species, as well as evaluating the potential volumes of biological resources) singly or as part of a group (in formation). At the same time, the trajectories of these aircraft are set by smooth spatial curves - parametric splines of the third order, which makes it easy to adjust the specified trajectories during the mission. In order to maintain a high speed of movement of vehicles along trajectories with high accuracy of movement and saving formation, it is proposed to adjust the specified speed directly during the mission in such a way that the thrusters can ensure their required movements, taking into account the restrictions on the thrust vectors. At the same time, a simplified model of the dynamics of a quadcopter was used to calculate the values of reference speeds, taking into account the influence of wind force, environmental resistance, gravity and the total thrust vector of the propellers. The systems synthesized on the basis of this method can be implemented even on low-power onboard computing devices of unmanned aerial vehicles. © 2024 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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An Improved DeeplabV3+ Tile Image Positioning Method

An Improved DeeplabV3+ Tile Image Positioning Method

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2024 International Conference Optoelectronic Information and Optical Engineering, OIOE 2024

作者： Li, Xiaoyang Wang, Rui Tong, Xing Niu, Lianqiang Shenyang University of Technology Shenyang China Key Laboratory of Network 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 Shenyang China

ISBN: (数字)9781510688209

ISBN: (纸本)9781510688193

In order to improve the detection accuracy and efficiency of surface defects on ceramic tiles, a detection model based on DeepLabV3+and combined with MobileNetv2 for feature extraction was constructed. Using ECA attention mechanism and multi branch receptive field cascade fusion structure to expand the sampling range of global and local element features for the empty space pyramid pooling module ASPP of the original model. Meanwhile, the model decoder uses depthwise separable convolutions instead of the original standard convolutions. Experimental results have shown that the improved model has an MPA value of 96.12%, a MIou value of 97.29%, an F1 value of 90.03%, and an Accuracy value of 99.89%. Compared with the previous model, the improved model's indicators have increased by 4.07%, 4.44%, 2.04%, and 1.02%, respectively. The segmentation accuracy and detection speed have been significantly improved. The experimental results fully demonstrate that the algorithm proposed in this article can effectively complete the task of detecting surface defects on ceramic tiles. © 2025 SPIE.

关键词： Image segmentation

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Few-shot working condition recognition of a sucker-rod pumping system based on a 4-dimensional time-frequency signature and meta-learning convolutional shrinkage neural network

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Petroleum Science 2023年第2期20卷 1142-1154页

作者： Yun-Peng He Chuan-Zhi Zang Peng Zeng Ming-Xin Wang Qing-Wei Dong Guang-Xi Wan Xiao-Ting Dong State Key Laboratory of Robotics Shenyang Institute of AutomationChinese Academy of SciencesShenyangLiaoning 110016China Key Laboratory of Networked Control Systems Chinese Academy of SciencesShenyangLiaoning 110016China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of SciencesShenyangLiaoning 110169China University of Chinese Academy of Sciences Beijing100049China Shenyang University of Technology ShenyangLiaoning 110870China School of Automation and Electrical Engineering Shenyang Ligong UniversityShenyangLiaoning 110159China

The accurate and intelligent identification of the working conditions of a sucker-rod pumping system is necessary. As onshore oil extraction gradually enters its mid-to late-stage, the cost required to train a deep learning working condition recognition model for pumping wells by obtaining enough new working condition samples is expensive. For the few-shot problem and large calculation issues of new working conditions of oil wells, a working condition recognition method for pumping unit wells based on a 4-dimensional time-frequency signature (4D-TFS) and meta-learning convolutional shrinkage neural network (ML-CSNN) is proposed. First, the measured pumping unit well workup data are converted into 4D-TFS data, and the initial feature extraction task is performed while compressing the data. Subsequently, a convolutional shrinkage neural network (CSNN) with a specific structure that can ablate low-frequency features is designed to extract working conditions features. Finally, a meta-learning fine-tuning framework for learning the network parameters that are susceptible to task changes is merged into the CSNN to solve the few-shot issue. The results of the experiments demonstrate that the trained ML-CSNN has good recognition accuracy and generalization ability for few-shot working condition recognition. More specifically, in the case of lower computational complexity, only few-shot samples are needed to fine-tune the network parameters, and the model can be quickly adapted to new classes of well conditions.

关键词： Few-shot learning Indicator diagram Meta-learning Soft thresholding Sucker-rod pumping system Time–frequency signature Working condition recognition

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Advances and Challenges in Large Model Compression: A Survey 24

Advances and Challenges in Large Model Compression: A Survey

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2024 Guangdong-Hong Kong-Macao Greater Bay Area International Conference on Digital Economy and Artificial Intelligence, DEAI 2024

作者： Xu, Yingying Song, Chunhe Sun, Yong Yu, Shimao 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 Shenyang China University of Chinese Academy of Sciences Beijing100049 China

ISBN: (纸本)9798400717147

With the development of computer technology, large-scale models have gradually evolved from early simple algorithms to today's complex deep neural networks with huge parameter scale and high computational complexity. These large-scale models have greatly advanced the artificial intelligence technology, which has realized revolutionary progress in the fields of image, speech, text and so on. However, the computational and storage requirements of large-scale models are also growing rapidly, which seriously constrains their deployment and application in computing resource-constrained environments. In order to solve this problem, model compression technology has emerged and has been greatly developed. In this paper, we systematically review the key technologies, application scenarios, challenges and future directions of large-scale model compression from the perspective of model compression technology. Our work aims to provide practitioners and researchers with detailed references on the development of the technology, and emphasizes the important role of model compression technology in promoting the development of lightweight artificial intelligence. © 2024 Owner/Author.

关键词： Deep neural networks

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DEGAS - Deformation Estimation based on Magnetic Gradient Tensor Contraction for Soft Robot Shape Servoing

DEGAS - Deformation Estimation based on Magnetic Gradient Te...

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IEEE International Conference on Soft robotics (RoboSoft)

作者： Jelena Vuletić Bruno Marić Matko Orsag LARICS Laboratory for Robotics and Intelligent Control Systems University of Zagreb Faculty of Electrical Engineering and Computing Zagreb Croatia

ISBN: (数字)9798331520205

ISBN: (纸本)9798331520212

This work proposes the first derivation, implementation, and experimental validation of magnetic-based proprioceptive sensing method for soft robotic applications. In our proposed approach, the magnetic sensing system measures gradient tensor contractions that can be directly related to the shape of a deformable plastering tool. Custom-designed and 3D-printed plastering tool embeds two identical permanent magnets that generate a non-symmetric magnetic field tracked by the proposed sensor. Seamless real-time control is enabled with the sensor sampling rate of 1 kHz. Classical linear control is synthesized for the scraper bending angle and orientation control. The tool, sensor, and the proposed control system are validated on robotic plastering and painting tasks.

关键词： Magnetic field measurement Tensors Deformation Shape Propioception Estimation Bending Soft robotics Sensors Painting

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Graph-Based Decentralized Exploration and Semantic Inspection for Multi-Robot systems

Graph-Based Decentralized Exploration and Semantic Inspectio...

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International Conference on Unmanned Aircraft systems (ICUAS)

作者： Nada E. Abbas Tamara Petrovic Faculty of Electrical Engineering and Computing LARICS Laboratory for Robotics and Intelligent Control Systems University of Zagreb Zagreb Croatia

ISBN: (数字)9798331513283

ISBN: (纸本)9798331513290

This paper presents a decentralized graph-based exploration and inspection framework for Multi-Robot systems, designed to address challenges in subterranean and largescale environments. Unlike prior works that focus solely on exploration or inspection, this framework integrates volumetric exploration, semantic inspection, and dynamic task allocation into a unified decentralized system. A key novelty of this work is the seamless integration of these modules in a multi-robot setting, allowing UAVs to autonomously coordinate their tasks without relying on centralized control. The framework employs a hierarchical graph structure, utilizing a dense local graph for immediate navigation and a sparse global graph for long-term planning and repositioning. Extensive simulations in large-scale complex-shaped environments demonstrate that the proposed approach improves the completeness of the generated maps, reduces inconsistencies in the constructed mesh, and accelerates the overall exploration-inspection process compared to existing decentralized strategies.

关键词： Semantics Inspection Prediction algorithms Dynamic scheduling Aircraft navigation Robustness Planning Multi-robot systems Resource management Centralized control

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The System of Coordinated Operation of Two Underwater Vehicles in a Complex Environment

The System of Coordinated Operation of Two Underwater Vehicl...

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2023 International Conference on Ocean Studies, ICOS 2023

作者： Filaretov, Vladimir Katsurin, Alexey Institute of Automation and Control Processes Feb Ras Vladivostok State University Laboratory of Robotic Systems Laboratory of Automation and Robotics Vladivostok Russia Far Eastern Federal University M.D. Ageev Institute for Marine Technology Problems Feb Ras Laboratory of Intelligent Information Systems for Marine Robots Department of Automation and Robotics Vladivostok Russia

ISBN: (纸本)9798350382457

The paper discusses methods of coordinated operation of two autonomous underwater vehicles, one of which is equipped with a multi-link manipulator and a vision system, and the second - auxiliary - only a vision system. These methods ensure the joint operation of two autonomous underwater vehicles both in the mode of semi-automatic positional remote control, and in the mode of automatic execution of operations with various objects. At the same time, work is considered in situations when the vision system of the main underwater vehicle does not allow observing the object of work, which is nevertheless located in the working area of the manipulator. In this case, the auxiliary inspection underwater vehicle with its own vision system is used to monitor the object. In the semi-automatic remote control mode, the manipulator automatically takes into account the current spatial orientation of the optical axis of the vision system of the inspection underwater vehicle, as well as the spatial orientations of both underwater vehicles at yaw angles in the absolute coordinate system. And in automatic mode, an accurate transfer of the spatial location and orientation of the object, which are determined using the vision system of the inspection underwater vehicle, is additionally provided to the associated coordinate system of the main underwater vehicle. It is possible to identify and eliminate errors that occur during the operation of the vision system and navigation systems of both underwater vehicles. The results of experimental studies have confirmed the operability of the proposed methods. © 2023 IEEE.

关键词： Autonomous underwater vehicles

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Local Path Planning Combined with the Motion State of Dynamic Obstacles 1

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17th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2022

作者： Hu, Yuxin Li, Jun Jiang, Lin Key Laboratory of Metallurgical Equipment and Control Technology Wuhan University of Science and Technology Wuhan430081 China Institute of Robotics and Intelligent Systems Wuhan University of Science and Technology Wuhan430081 China

ISBN: (数字)9789819915491

ISBN: (纸本)9789819915484

Aiming at the problem that the current local path planning algorithm treats moving obstacles as transient static ones when avoiding obstacles, lacking initiative and security, a local path planning algorithm combining dynamic obstacle motion state is proposed. Firstly, the position information of all obstacles is obtained by a single scan LIDAR. Then, segmenting and linearly fitting all laser point clouds, removing the known obstacles in the map;and marking possible emerging dynamic obstacles with circles of appropriate size;then detecting the dynamic obstacles through the change of the coordinates of the center of the circle, obtaining the center coordinates of the dynamic obstacles continuously;thus, the equation of motion is solved by using the least squares. Finally, the cost map of dynamic obstacles is expanded in the direction of velocity, by combining DWA dynamic window method to realize avoiding dynamic obstacles safely. In this paper, through the simulation experiments and real environment experiments of robot meeting scenes from multiple angles, the results show that expanding the cost map of the motion direction of the dynamic obstacles provides more sufficient response space for the robot to avoid the dynamic obstacles. Compared with the original DWA, the algorithm in this paper can avoid dynamic obstacles more safely, which proves the security and feasibility of this algorithm. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Equations of motion

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Characteristics of laser-induced breakdown spectroscopy of liquid slag

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Plasma Science and Technology 2024年第2期26卷 86-93页

作者：董长言于洪霞孙兰香李洋刘修业周平黄少文 State Key Laboratory of Robotics Shenyang Institute of AutomationChinese Academy of SciencesShenyang 110016People's Republic of China Key Laboratory of Networked Control Systems Chinese Academy of SciencesShenyang 110016People's RepublicofChina Institutes for Robotics and Intelligent Manufacturing Chinese Academy of SciencesShenyang 110169People's Republic of China Shenyang University of Technology Shenyang 110870People's Republic of China Shenyang Ligong University Shenyang 1i0142People's Republic of China Shandong Iron and Steel Company Ltd. Jinan 271105People's Republic of China

Rapid online analysis of liquid slag is essential for optimizing the quality and energy efficiency of steel production. To investigate the key factors that affect the online measurement of refined slag using laser-induced breakdown spectroscopy(LIBS), this study examined the effects of slag composition and temperature on the intensity and stability of the LIBS spectra. The experimental temperature was controlled at three levels: 1350℃, 1400℃, and 1450℃. The results showed that slag composition and temperature significantly affected the intensity and stability of the LIBS spectra. Increasing the Fe content and temperature in the slag reduces its viscosity, resulting in an enhanced intensity and stability of the LIBS spectra. Additionally, 42 refined slag samples were quantitatively analyzed for Fe, Si, Ca, Mg, Al, and Mn at 1350℃, 1400℃, and 1450℃.The normalized full spectrum combined with partial least squares(PLS) quantification modeling was used, using the Ca Ⅱ 317.91 nm spectral line as an internal standard. The results show that using the internal standard normalization method can significantly reduce the influence of spectral fluctuations. Meanwhile, a temperature of 1450℃ has been found to yield superior results compared to both 1350℃ and 1400℃, and it is advantageous to conduct a quantitative analysis of the slag when it is in a “water-like” state with low viscosity.

关键词： laser-induced breakdown spectroscopy(LIBS) slag temperature composition viscosity internal standard normalization partial least squares(PLS)

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A Weighting Factors Autotuning Strategy for Model Predictive Torque control of Permanent Magnet Synchronous Motor Based on Adaptive Multi-Objective Black Hole Algorithm 42

A Weighting Factors Autotuning Strategy for Model Predictive...

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42nd Chinese control Conference, CCC 2023

作者： Zhou, Zixiang Wu, Tao School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China System Integration and Industrial Robotics Laboratory Wuhan430074 China

ISBN: (纸本)9789887581543

The rational design of weighting factors in the cost function for finite control set model predictive torque control (FCS-MPTC) has been a matter of great interest in power electronics and electrical drives. In order to solve this problem, a weighting factors autotuning strategy for FCS-MPTC of permanent magnet synchronous motor (PMSM) based on the adaptive multi-objective black hole algorithm (AMOBH) is proposed. In this paper, the design process of the FCS-MPTC algorithm is first analyzed in detail. Then, an AMOBH algorithm that can take into account both population convergence and population diversity is introduced, and based on this algorithm, the design problem of the weighting factors is successfully transformed into a multi-objective optimization problem by means of reconstructing the cost function and designing the motor operation information collected in real time as the objective functions of the multi-objective optimization algorithm. Simulation results show that the proposed method can find a set of weighting factor combinations suitable for different working condition requirements, and these weighting factors can effectively improve the operation performance of the PMSM system. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Cost functions

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