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Distribution-Allowed Noise-Resistant Neural Dynamics for Constrained Time-Dependent Quadratic Programming With kWTA Application

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IEEE Transactions on Systems, Man, and Cybernetics: Systems 2025年第5期55卷 3732-3741页

作者： Ma, Xin Ma, Dexiu Liu, Mei The Chinese University of Hong Kong Multi-Scale Medical Robotics Center Department of Mechanical and Automation Engineering Hong Kong Dingxi Vocational and Technical College School of Electronic Information Dingxi730500 China

Existing computational models for addressing time-dependent quadratic programming (TDQP) problems encounter some challenges, such as generating lagging errors, lack of noise immunity, and inability to be distributed. To handle these challenges, this article proposes a distribution-allowed noise-resistant neural dynamics (DANRND) model to solve TDQP problems with equality and inequality constraints by introducing auxiliary variables rather than by using the nonlinear complementary problem (NCP) function. The proposed model is able to effectively eliminate the hysteresis error and suppress the influence of noises. Specifically, the proposed model is capable of implementation in a distributed manner, which extends its scope of applications. Then, theoretical analyses are provided to prove the global convergence in both noise-free and noisy conditions. Simulative examples and comparison results with existing methods are offered, demonstrating the superiority of the proposed DANRND model. Finally, a distributed cooperative task based on the k-winner-take-all (kWTA) operation is performed on a multirobot platform to further verify the distributed implementation of the proposed DANRND model. © 2013 IEEE.

关键词： Quadratic programming

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Carbon dioxide storage and cumulative oil production predictions in unconventional reservoirs applying optimized machine-learning models

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Petroleum Science 2025年第1期22卷 296-323页

作者： Shadfar Davoodi Hung Vo Thanh David A.Wood Mohammad Mehrad Sergey V.Muravyov Valeriy S.Rukavishnikov School of Earth Sciences & Engineering Tomsk Polytechnic University Laboratory for Computational Mechanics Institute for Computational Science and Artificial Intelligence Van Lang University Applied Science Research Center Applied Science Private University DWA Energy Limited Division for Automation & Robotics Tomsk Polytechnic University

To achieve carbon dioxide（CO2） storage through enhanced oil recovery, accurate forecasting of CO2subsurface storage and cumulative oil production is essential. This study develops hybrid predictive models for the determination of CO2storage mass and cumulative oil production in unconventional reservoirs. It does so with two multi-layer perceptron neural networks（MLPNN） and a least-squares support vector machine（LSSVM）, hybridized with grey wolf optimization（GWO） and/or particle swarm optimization（PSO）. Large, simulated datasets were divided into training（70%） and testing（30%）groups, with normalization applied to both groups. Mahalanobis distance identifies/eliminates outliers in the training subset only. A non-dominated sorting genetic algorithm（NSGA-II） combined with LSSVM selected seven influential features from the nine available input parameters: reservoir depth, porosity,permeability, thickness, bottom-hole pressure, area, CO2injection rate, residual oil saturation to gas flooding, and residual oil saturation to water flooding. Predictive models were developed and tested,with performance evaluated with an overfitting index（OFI）, scoring analysis, and partial dependence plots（PDP）, during training and independent testing to enhance model focus and effectiveness. The LSSVM-GWO model generated the lowest root mean square error（RMSE） values（0.4052 MMT for CO2storage and 9.7392 MMbbl for cumulative oil production） in the training group. That trained model also exhibited excellent generalization and minimal overfitting when applied to the testing group（RMSE of0.6224 MMT for CO2storage and 12.5143 MMbbl for cumulative oil production）. PDP analysis revealed that the input features “area” and “porosity” had the most influence on the LSSVM-GWO model's prediction performance. This paper presents a new hybrid modeling approach that achieves accurate forecasting of CO2subsurface storage and cumulative oil production. It also establishes a new standard for such forecasting,

关键词： Hybrid machine learning Least-squares support vector machine Grey wolf optimization Feature selection Carbon dioxide storage Enhanced oil recovery

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Path Integral Policy Improvement and Dynamic Movement Primitives Fusion Based Impedance Force Control with Error Loop Correction

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IEEE Transactions on automation Science and Engineering 2025年 22卷 15034-15044页

作者： Liu, Mujie Chen, Haifei Li, Lijun Ma, Zhiqiang Xu, Yong Zhang, Hui Central South University of Forestry and Technology National Forestry and Grassland Engineering Technology Research Center for Harvesting Equipment of Nonwood Forest Fruits and Engineering Research Center for Forestry Equipment of Hunan Province School of Mechanical and Intelligent Manufacturing Changsha410004 China Northwestern Polytechnical University Research Center for Intelligent Robotics School of Astronautics Xi'an710072 China Beijing Institute of Technology School of Automation Beijing100081 China Hunan University National Engineering Research Center of Robot Visual Perception and Control Technology School of Robotics Changsha410082 China

Path Integral Strategy Improvement (PI2)-based impedance control is a superior scheme for preventing damage to the physical structure of the fruit during the harvesting process. However, it is highly sensitive to disturbances and has limited generalization ability during the parameter learning process, making it difficult to apply the correct gripping force to fruits with uncertain stiffness. To solve this problem, this paper proposes a variable impedance force control method that integrates PI2 with Dynamic Movement Primitives (DMPs), supplemented by a force error correction loop. Firstly, an adaptive impedance parameter matching mechanism based on gain schedules is designed to facilitate dynamic estimation of impedance parameters and enable precise force control. To further accelerate impedance parameter matching in unknown environments, the PI2 algorithm is introduced to optimize gain schedules, and DMPs are integrated to suppress disturbances, thereby improving the generalization ability of the impedance model's parameter learning. In addition, an additional force error control loop has been designed to minimize the deviation between the desired and actual gripping force. Finally, the effectiveness of the proposed method is verified through simulation and experiment in fruit teleoperation picking robot. © 2025 IEEE.

关键词： Rotation

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Video Streaming Protocols Comparison in Field Experiments for Aerial Teleoperation

Video Streaming Protocols Comparison in Field Experiments fo...

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9th International Conference on Mechanical Engineering and robotics Research, ICMERR 2025

作者： Fernandez, Manuel J. Franceschini, Riccardo Becerra, Julian Cayero Fumagalli, Matteo Technical University of Denmark Department of Electrical Engineering Automation and Control Kongens Lyngby2800 Denmark Robotics and Automation Unit Eurecat Technology Center of Catalunya Cerdanyola Del Vallès Barcelona Spain

ISBN: (纸本)9798331509262

As aerial robots evolve to perform complex tasks such as manipulation and visual inspection, maintaining the pilot at the center of decision-making is critical for mission safety and leveraging human expertise. A key enabler of this collaboration is reliable video streaming between the robot and the operator. This paper presents a comparative analysis of four video streaming protocols RTP (Real-time Transport Protocol), RTSP (Real-Time Streaming Protocol), SRT (Secure Reliable Transport), and ROSTCP (ROS Transport Control Protocol) based on extensive field experiments. The evaluation focuses on CPU usage, network throughput, latency, streaming quality, and packet integrity across varying distances. Tools such as iperf, ping, GStreamer, and Wireshark were employed for detailed performance measurements. Results reveal significant differences: SRT and RTP deliver superior network stability and resilience to packet loss, while RTSP and ROSTCP show advantages in CPU efficiency. These findings provide actionable insights for optimizing video streaming in aerial robotics, emphasizing the trade-offs and advantages of each protocol in real-world scenarios. © 2025 IEEE.

关键词： Social robots

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Leakage Source Localization Based on Improved-Infotaxis 16th

Leakage Source Localization Based on Improved-Infotaxis

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16th International Conference on Modelling, Identification and Control, ICMIC 2024

作者： Tao, Xiang Cheng, Lei Yao, Tianxiao Engineering Research Center for Metallurgical Automation and Measurement Technology of Ministry of Eduction Wuhan430081 China Institute of Robotics and Intelligent Systems Wuhan University of Science and Technology Wuhan430081 China

ISBN: (纸本)9789819617760

In recent years, with the rapid development of the chemical industry, the risks in this field are also increasing, in which the leakage of hazardous gases can cause serious harm to both people and the environment, so it is crucial to locate the leakage source quickly and accurately. For pollution source traceability, the traditional gradient algorithm is prone to fall into local optimization, and the infotaxis algorithm is biased towards exploration, which is prone to waste time cost and control cost. We propose a new strategy to balance the exploration and utilization in the search process by studying the effects of multiple algorithms and setting different experimental parameters (gas release rate and wind speed) on the overall performance, and the experimental results show that the algorithm has a strong performance under different environmental variables with strong robustness. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Chemical industry

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Visual-Lidar Odometry with Orientation Correction towards Millimeter-Level Localization for Indoor Construction Robots

Visual-Lidar Odometry with Orientation Correction towards Mi...

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2025 IEEE/SICE International Symposium on System Integration, SII 2025

作者： Hisatsugu, Hiroki Koshizuka, Hisahiro Hori, Moritoyo Yamamoto, Kenjiro Center for Sustainability Hitachi Ltd. Connective Automation Innovation Center Robotics Research Department Japan Hitachi Channel Solutions Corp. Channel Business Promotion Center Sales Department Japan Hitachi Channel Solutions Corp. Channel Business Promotion Center Products Development Department Japan

ISBN: (纸本)9798331531614

We propose a high-precision odometry method that fuses visual-lidar odometry with orientation information estimated by ceiling line features, aiming to achieve millimeter-level localization required at construction sites. Visual-Lidar Odometry and Mapping has demonstrated top-class accuracy with an error of 50 mm in benchmarks. However, when evaluated in environments with large open walls, such as indoor construction sites with few shape and image features, the method was found to be less accurate primarily due to errors in the orientation estimation. To address this issue, we propose a method that combines the use of ceiling line features to estimate the robot's orientation angle, thereby improving the accuracy of the odometry position estimates. We evaluated the accuracy using a real robot in an environment similar to a construction site and achieved an average error of 6.2 mm (straight-line route), 7.6 mm (rectangular route), surpassing the accuracy of conventional methods. These results confirm the effectiveness of utilizing orientation correction from ceiling line features. © 2025 IEEE.

关键词： Ceilings

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High-precision magnetic field measurement system based on a coherent population trapping magnetometer onboard the SATech-01 satellite

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Science China(Technological Sciences) 2025年第2期68卷 227-242页

作者： Hongbo XUE Wei SONG Haoran ZHAO Yiteng ZHANG Shanzhi YE Jindong WANG Ran TAO Peng SANG Keli CHEN Xingzi BI Bingjun CHENG Bin ZHOU Yongliang XUE Yingying TANG Liu LIU Jinsong LI Xiaocheng ZHU Baoquan LI Jinguo LIU Wen CHEN Xiaofeng ZHANG Yonghe ZHANG Lei LI State Key Laboratory of Space Weather National Space Science CenterChinese Academy of SciencesBeijing 100190China Key Laboratory of Solar Activity and Space Weather National Space Science CenterChinese Academy of SciencesBeijing 100190China Key Laboratory of Electronics and Information Technology for Space Systems National Space Science CenterChinese Academy of SciencesBeijing 100190China State Key Laboratory of Robotics Shenyang Institute of AutomationChinese Academy of SciencesShenyang 110016China Innovation Academy for Microsatellites Chinese Academy of SciencesShanghai 201304China

On July 27,2022,a high-precision system for measuring the magnetic field based on a coherent population trapping magnetometer(referred to as the CPT system)was launched onboard the Space Advanced Technology demonstration satellite(SATech-01)by a ZK-1A *** payload comprises a scalar coherent population trapping magnetometer(CPTM),triaxial anisotropic magnetoresistance magnetometer(AMRM),and nano star tracker mounted on a non-magnetic telescopic tubular *** configuration enables synchronized measurement of scalar and vector geomagnetic fields,as well as the attitude,making the payload with its compact sensors suitable for applications on miniature satellite *** November 7,2022,the novel telescopic tubular mast was deployed in orbit,extending to a length of 5.28 *** CPTM,an absolute scalar magnetometer with an omnidirectional sensor,is the first China-developed quantum/atomic magnetometer successfully operating in *** orbit,the CPTM has sensitivity of~10 pT/Hz^(1/2) and can automatically operate under complex magnetic field *** difference between the scalar fields obtained using the CPTM and CHAOS model has a mean deviation of -3.73 nT and a standard deviation of 26.11 nT(1σ),without on-orbit calibration or *** miniaturized AMRM has a sensitivity of~0.3 nT/Hz^(1/2) and maintains stable and reliable operation in *** low-power and miniaturized nano star tracker has a measurement uncertainty of 14.23″(1σ)in *** mission has realized the on-orbit technical verification of the integrated and synchronized detection of the vector magnetic field and attitude and fully validated the system’s performance,automation level,and reliability.

关键词： magnetic field measurement system coherent population trapping magnetometer anisotropic magnetoresistance magnetometer nano star tracker non-magnetic telescopic tubular mast satellite

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Hyperparameter Tuning of Convolution Neural Network for Paddy Leaves Disease Detection

Hyperparameter Tuning of Convolution Neural Network for Padd...

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5th International Conference on Emerging Electrical Energy, Electronics and Computing Technologies, ICE4CT 2024

作者： Yusoff, C.M.Y.A. Che Mat Nadzri, N.Z. Yusoff, Y. UniKL Robotics and Industrial Automation Center Universiti Kuala Lumpur Malaysia France Institute Selangor Bangi Malaysia

The traditional approach to identifying paddy leaf diseases in Malaysia's agriculture sector involves visual inspection by farmers or agricultural experts. However, this method heavily relies on human expertise to recognize visual symptoms like discoloration, spots, or lesions on the leaves, leading to subjective assessments and delayed diagnosis. While various deep learning models have been utilized to detect paddy leaf diseases, there is a need for a more comprehensive discussion on the appropriate hyperparameters setting. This study focused on utilizing Convolutional Neural Network (CNN) models, specifically ResNet and VGG architectures, to identify paddy leaf diseases in Sekinchan, Selangor. The models were trained on a dataset consisting of both online and real-world images, which underwent several augmentation processes to enhance the model's robustness. The study has highlighted the optimal hyperparameters of the CNN model, resulting in an impressive accuracy rate of 98.71% and a minimal loss rate of 0.001. The integration of the final model into a specific Graphical User Interface has further enhanced its utility. © 2025 Institute of Physics Publishing. All rights reserved.

关键词： Graphical user interfaces

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Semi-Autonomous Navigation Based on Local Semantic Map for Mobile Robot

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Journal of Shanghai Jiaotong university(Science) 2025年第1期30卷 27-33页

作者： ZHAO Yanfei XIAO Peng WANG Jingchuan GUO Rui Department of Automation Institute of Medical RoboticsShanghai Jiao Tong UniversityShanghai200240China State Key Laboratory of System Control and Information Processing Ministry of Education of ChinaShanghai200240China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240China State Grid Intelligence Technology Co. Ltd.Jinan250013China

Mobile robots represented by smart wheelchairs can assist elderly people with mobility *** paper proposes a multi-mode semi-autonomous navigation system based on a local semantic map for mobile robots,which can assist users to implement accurate navigation(e.g.,docking)in the environment without prior *** order to overcome the problem of repeated oscillations during the docking of traditional local path planning algorithms,this paper adopts a mode-switching method and uses feedback control to perform docking when approaching semantic *** last,comparative experiments were carried out in the real *** show that our method is superior in terms of safety,comfort and docking accuracy.

关键词： semi-autonomous navigation mobile robot semantic map voice interaction

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Frequency shift-based 3D shape measurement in the presence of strong inter-reflection

Frequency shift-based 3D shape measurement in the presence o...

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2024 International Conference on Optical and Photonic Engineering, icOPEN 2024

作者： Miao, Huisi Liu, Wan Yan, Ziyu Xu, Weidong Zhang, Dongbo Zhang, Hui School of Automation and Electronic Information Xiangtan University Xiangtan411105 China Xiangtan Electric Manufacturing Co..Ltd. Xiangtan411105 China National Engineering Research Center of Robot Visual Perception and Control Technology School of Robotics Hunan University Changsha410082 China

ISBN: (数字)9781510688117

ISBN: (纸本)9781510688100

Traditional fringe projection profilometry (FPP) struggles with robust imaging and high-precision three-dimensional (3D) reconstruction in complex lighting environments with strong inter-reflection. This paper proposes a method combining frequency-shifted fringe projection and epipolar constraint to achieve high-precision 3D profilometry in such scenarios. First, environmental light interference is mitigated and the maximum fringe frequency is reduced through window function analysis (WFA) and a four-step phase-shifting (PS). Then, direct and indirect illumination are separated in the Fourier domain. Direct illumination positions are identified using threshold segmentation and epipolar geometry constraint, enhancing imaging robustness in strong inter-reflection contexts. Experimental results demonstrate that the method constructs direct and indirect illumination feature models, accurately obtaining direct illumination information and eliminating multi-path interference. Additionally, in tests with complex geometrical surfaces, imaging efficiency and robustness significantly improve, with effective point cloud data increasing by over 30% and planar accuracy improving by 50%. © 2025 SPIE.

关键词： Light interference

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