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Light field angular super resolution based on residual channel attention and classification up-sampling

Multimedia Tools and Applications 2025年第12期84卷 10945-10967页

作者： Wang, Xingzheng Wang, Zixuan You, Senlin College of Mechatronics and Control Engineering Shenzhen University Nanhai Avenue Guangdong Province Shenzhen518060 China

Current light field angular super resolution algorithms generate coarse viewpoint images due to their low learning ability and equally upsample all macropixels on the light field image. In this paper, we propose a novel angular super resolution network to precisely enhance angular resolution, via stacking multiple residual channel attention groups and accurately up-sampling macro pixels with a classified prediction module. Firstly, the network extracts low-frequency angular information on the input light field image, and then refines high-frequency angular information by stacking residual channel attention groups. Secondly, the classified prediction module combines high-frequency and low-frequency angular information to predict three groups of feature maps with three channels. The first two channels of each group predict two different angular information from macro pixels. The third channel learns classification results and ensures up-sampling bases on the most accurate information. According to classified results, we could accurately speculate occlusions, and obtain three high-quality images with the same angular resolution as the input image. Finally, to enhance the angular resolution, we integrate three high-quality images with the input image into one light field image. The experimental results verify the effectiveness of our proposed method, we achieve average PSNR gains of 2.81 dB than the state-of-the-art method. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Forecasting

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Dual-Mode Model Predictive control for Constrained Networked control System with DoS Attacks and Disturbances

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IEEE Transactions on Automation Science and engineering 2025年 22卷 14987-14996页

作者： Qiu, Li Shao, Zhixing Dong, Lingtao Bai, Xiaoshan Shenzhen University College of Mechatronics and Control Engineering Shenzhen518060 China

A dual-mode model predictive control (MPC) strategy is tailored for a networked control system (NCS) operating in a constrained environment that is vulnerable to additive disturbances as well as denial-of-service (DoS) attacks. DoS attacks disrupt communication, affecting data and control signals. This article optimizes and improves the traditional MPC strategy to solve the problems caused by DoS attacks on the system. A robustness constraint with scaling parameters is introduced to efficiently handle uncertainty in the MPC algorithm. The control strategy proposed in this article enables a dynamic shift in control modes. When the system state enters a predefined set, the control strategy transitions from optimization to a state feedback control law. In order to analyze the recursive feasibility of the optimization problem and system stability, the relationship between the system errors, disturbances, and DoS attacks is derived. We also derive conditions on disturbance upper bound, DoS attack maximum allowable duration, and scaling parameters should be satisfied to ensure the recursive feasibility of the optimization problem and system stability. © 2004-2012 IEEE.

关键词： Networked control systems

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Study on Dry Electrical Discharge Assisted Grinding of SiCp/Al Composite

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Chinese Journal of Mechanical engineering 2025年第1期38卷 106-118页

作者： Yanjun Lu Yuming Huang Xiaobu Liu Rong Cheng Shunda Zhan Guangdong Provincial Key Laboratory of Micro/Nano Optomechatronics Engineering College of Mechatronics and Control EngineeringShenzhen UniversityShenzhen 518060China School of Intelligent Manufacturing and Equipment Shenzhen Institute of Information TechnologyShenzhen 518172China

SiC-reinforced aluminum matrix(SiCp/Al)composite is widely utilized in the aerospace,automotive,and electronics industries due to the combination of ceramic hardness and metal ***,the significant disparity in properties between SiC particles and the aluminum matrix results in severe tool wear and diminished surface quality during conventional *** study proposes an environmentally friendly and clean dry electrical discharge assisted grinding process as an efficient and low-damage machining method for SiCp/*** experimental platform was set up to study the impact of grinding and discharge process parameters on surface *** study compared the chip formation mechanism and surface quality between dry electrical discharge assisted grinding and conventional grinding,revealing relationships between surface roughness,grinding force,grinding temperature,and related *** results indicate that the proposed grinding method leads to smaller chip sizes,lower grinding forces and temperatures,and an average reduction of 19.2%in surface roughness compared to conventional *** axial,tangential,and normal grinding forces were reduced by roughly 10.5%,37.8%,and 23.0%,*** optimized process parameters were determined to be N=2500 r/min,vf=30 mm/min,a=10μm,E=15 V,f=5000 Hz,dc=80%,resulting in a surface roughness of 0.161μm.

关键词： Dry electrical discharge assisted grinding SiCp/Al composite Surface quality Grinding force Grinding temperature

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Fabrication of hydrophobic zirconia ceramic mould inserts through the integration of self-assembled monolayer modification and stereolithography 3D printing technology

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Ceramics International 2025年第9期51卷 11121-11135页

作者： Lou, Yan Yu, Qingke Yu, Jiangtao Qv, Piao Huang, Guijian Liu, Mingyu Guangdong Key Laboratory of Micro-Nano-Opto-Mechatronics Engineering Technology College of Mechatronics and Control Engineering Shenzhen University Shenzhen518060 China School of Engineering & Physical Sciences University of Lincoln LincolnLN6 7TS United Kingdom

Microstructured ceramic mould inserts face significant challenges in practical applications due to their hydrophilicity. Self-assembled monolayers (SAMs), recognized as a promising surface modification technology for micro-nanostructured surfaces, offer a potential solution to this issue. Meanwhile, stereolithography (SLA) 3D printing, with its exceptional flexibility and precise manufacturing capabilities for complex structures, is particularly well-suited for applications in micro-nanostructured moulds. This study proposes a novel method for fabricating hydrophobic zirconia microstructured mould inserts by combining SLA 3D printing with SAM modification. The results show that phosphonic acid SAMs significantly reduce the surface free energy of zirconia ceramics, transforming the surface from hydrophilic to hydrophobic and increasing the water contact angle by 114.8 %. Compared to commercial zirconia ceramics, SAM technology demonstrates superior modification effects on 3D-printed zirconia surfaces, achieving over twofold improvements in hydrophobicity and frictional properties. Among the three SAMs with varying chain lengths, short-chain hexyl phosphonic acid (HPA) SAMs exhibit the highest molecular packing density and order. Additionally, phosphonic acid SAMs significantly reduce the friction coefficient of 3D-printed zirconia, effectively minimizing surface fatigue and wear while enhancing wear resistance. The study identifies molecular packing density and order as critical factors influencing surface wettability, friction performance, and stability, with these properties improving consistently with greater packing density and order. Finally, zirconia microstructured mould inserts modified with HPA SAMs successfully injection-moulded polypropylene (PP) micro-cylinders with a diameter of 650 μm and a height of 1195 μm, achieving automatic demoulding. This study highlights the potential of 3D-printed zirconia moulds in practical applications, offering new directio

关键词： Stereolithography

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EAT: epipolar-aware Transformer for low-light light field enhancement

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Multimedia Tools and Applications 2025年第12期84卷 10609-10630页

作者： Wang, Xingzheng Huang, Wenhao Chen, Kaiqiang Wang, Zixuan Deng, Yuanlong College of Mechatronics and Control Engineering Shenzhen University Yuehai Street Guangdong Shenzhen518060 China Shenzhen Institute of Technology Jiangjunmao Road Guangdong Shenzhen518116 China

Current low-light light field (LF) enhancement methods are mainly based on the convolutional neural network and have achieved considerable effect. However, these methods only consider neighboring views or local epipolar plane images (EPIs), which neglect the rich epipolar geometry among all views and fail to restore more texture details. In this paper, we deliberate the epipolar geometry and take effective utilization of epipolar geometry as a principle to design an epipolar-aware Transformer (EAT). On the one hand, we develop a global epipolar geometry (GEG) structure by processing all views in different epipolar directions respectively to efficiently extract epipolar geometry. On the other hand, in order to exploit epipolar geometry further, we propose an attention-based view selection strategy employing the Transformer to generate attention maps across views and focus on more significant views in the corresponding directions. Specially, EAT consists of two stages: in Stage-I, all views are processed based on GEG structure and selectively fused into the global representation. And in Stage-II, the global information is fine-tuned to self-adaptively enhance each view based on their different angular positions. Experimental results on three publicly available LF datasets show that the proposed method outdoes the state-of-the-art methods by 0.797 dB in average PSNR gain. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Textures

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Design and coring performance analysis of handheld and machine-based composite lunar soil coring device

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Advances in Space Research 2025年第11期75卷 8287-8303页

作者： Zhang, Xu Zhang, Guoqing Wang, Yaohui Gao, Mingzhong Song, Lei Wang, Chang Xie, Heping College of Mechatronics and Control Engineering Shenzhen University Guangdong Shenzhen518060 China State Key Laboratory of Intelligent Construction and Healthy Operation and Maintenance of Deep Underground Engineering Shenzhen University Guangdong Shenzhen518060 China

Sampling and exploration of the Moon is an important means of further developing lunar resources and is of great significance in solving future problems such as the shortage of resources on Earth. Facing the increasingly complex mission requirements and challenges of the lunar exploration project, a composite multifunctional coring device capable of sampling deeper on the lunar surface is needed. Therefore, this paper innovatively proposes a lunar soil coring device program, aiming to research deep stratigraphic preservation sampling technology. The design of this coring device combines the advantages of handheld and machine-based methods to improve coring efficiency. In addition, coring simulation experiments of lunar soil particles based on the discrete element method (DEM) clarified that the assisted impact can improve the coring performance of the device to a certain extent. Finally, according to the designed coring device to construct the corresponding test platform, analyze the influence of different coring methods on the coring performance of the device. Meanwhile, the research results of this paper can provide theoretical and technical support for the subsequent lunar sampling exploration program. © 2025 COSPAR

关键词： Stratigraphy

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A Lyapunov-Based Framework for Trajectory Planning of Wheeled Vehicle Using Imitation Learning

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IEEE Transactions on Automation Science and engineering 2025年 22卷 12118-12133页

作者： Lai, Jialun Wu, Zongze Ren, Zhigang Chen, Ci Tan, Qi Xie, Shengli Guangdong University of Technology School of Automation Guangdong Guangzhou510006 China Shenzhen University College of Mechatronics and Control Engineering Guangdong Shenzhen518052 China Zhejiang University State Key Laboratory of Industrial Control Technology Hangzhou310027 China

Trajectory planning with a learning-based approach has emerged as a crucial element in autonomous unmanned systems and has attracted substantial interest from both academia and industry. However, unresolved issues persist concerning data efficiency, safety, convergence, and generalization within the control pipeline. To address this gap, this work presents a trajectory planning method that combines the differential flatness of wheeled vehicle with global convergence property. Our proposed framework transforms the trajectory planning problem, integrating kinematic constraints into a motion planning paradigm. This transformation significantly reduces the state space associated with trajectory planning. Initially, Gaussian mixture regression (GMR) is employed to learn the nonlinear mapping from flat input, leveraging a limited number of demonstrations solved by the optimal control method. Subsequently, we design an asymmetric quadratic Lyapunov function that incorporates both random barrier information and the potential convergence property of the demonstration trajectories. Based on the optimized parameterized Lyapunov function incorporating the convergence and safety criteria, the analytical supplementary control is subsequently obtained by solving a quadratic programming problem to compensate for the prediction errors of GMR, which make the framework complete. Both numerical and real-world experiments are performed to validate the effectiveness of our framework. © 2004-2012 IEEE.

关键词： Motion planning

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DADAN: Dynamic-Augmented and Density-Aware Network for Accurate 3-D Object Detection With 4-D Radar

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IEEE Sensors Journal 2025年第6期25卷 10272-10286页

作者： Wang, Xingzheng Li, Jiahui Wu, Jianbin Wu, Shaoyong Li, Lihua Shenzhen University College of Mechatronics and Control Engineering Shenzhen518060 China Shenzhen Technology University Guangdong-Hongkong-Macao Critical Optical Components Precision Manufacturing Research Center Sino-German College of Intelligent Manufacturing Shenzhen518118 China

The cost-effective automotive 4-D radar is emerging as a feasible solution for 3-D object detection in autonomous driving scenarios. However, point clouds generated by 4-D radar are typically sparse. Current methods encounter challenges in resolving the foreground-background confusion in sparse point clouds due to: 1) the underutilization of the unique dynamic information (velocity and intensity) of 4-D radar points;and 2) the density variations of point clouds where they are near-dense-far-sparse, exacerbating the confusion. Therefore, we propose a dynamic-augmented and density-aware network (DADAN) to address these challenges by: 1) assigning high weights to foreground points based on dynamic information and enhancing their feature encoding to reduce confusion effectively;and 2) utilizing attention mechanisms along with density information to adaptively address exacerbated confusion caused by density variations. The DADAN comprises a dynamic-augmented encoding network, a density-aware backbone, and a detection head. The encoding network incorporates a dynamic-augmented encoding module (DAEM) that assigns high weights to foreground points based on velocity and intensity data to improve their feature encoding. Notably, foreground points typically exhibit distinct dynamic information compared to background points, distinguishing them from the background. The backbone network incorporates an attention mechanism along with density information to generate density-aware features. The detection head is responsible for 3-D bounding boxes and object categories. The experimental results on various public datasets demonstrate the superior performance of the proposed method compared to existing approaches. These results illustrate that the DADAN effectively addresses the issue of confusion, accurately detecting objects in complex scenes. © 2001-2012 IEEE.

关键词： Object detection

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Strong absorption in ultra-wide band by surface nano engineering of metallic glass

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Fundamental Research 2025年第1期5卷 307-314页

作者： Jianan Fu Xin Li Zhen Li Fei Sun Wenxin Wen Jinlai Zhao Wenqing Ruan Shuai Ren Zhenxuan Zhang Xiong Liang Jiang Ma Shenzhen Key Laboratory of High Performance Nontraditional Manufacturing College of Mechatronics and Control EngineeringShenzhen UniversityShenzhen 518060China College of Materials Science and Engineering Shenzhen Key Laboratory of Polymer Science and TechnologyGuangdong Research Center for Interfacial Engineering of Functional MaterialsShenzhen 518060China

Broadband light absorption is important for applications such as infrared detectors,solar energy collectors,and photothermal *** propose a facile and common strategy to fabricate light absorbers with strong ultra-wideband *** to their excellent thermoplastic forming ability,metallic glasses could be patterned into finely arranged nanowire arrays,which show extremely low reflectivity(∼0.6%)in the visible and near-infrared regimes,and a low reflectivity(∼15%)in the mid-infrared regime as caused by multiscale nano spacing,multiple reflections,and plasmonic *** strong absorption at surfaces with nanowires provides excellent photothermal conversion *** photothermal properties show that a surface with nanowires can be rapidly heated up to∼160°C at a rate of 28.75°C/s,which is 30 times higher than smooth ***,a surface with nanowires shows a high photothermal conversion efficiency(η_(PT)=56.36%).The fabricated metallic glass absorbers exhibit adaptability as they can be easily formed into various complex shapes and meet the requirements under harsh *** outcomes of our research open the door to manufacturing high-performance absorbers for applications in photothermal electric power generation,desalination,and photodetectors.

关键词： Metallic glass Nanoforming Ultra-wideband absorption Photothermal properties Thermoplastic forming

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Near-perfect replication on amorphous alloys through active force modulation based on machine learning/neural network parameter prediction

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Science China(Physics,Mechanics & Astronomy) 2025年第1期68卷 177-187页

作者： Senkuan Meng Zheng Wang Ruisong Zhu Ruijie Liu Jiang Ma Lina Hu Weihua Wang Key Laboratory for Liquid-Solid Structural Evolution and Processing of Materials(Ministry of Education) School of Materials Science and EngineeringShandong UniversityJinan 250061China College of Mechatronics and Control Engineering Shenzhen UniversityShenzhen 518060China Songshan Lake Materials Laboratory Dongguan 523808China Institute of Physics Chinese Academy of SciencesBeijing 100190China

As a microforming technique,micro/nano-structural replication possesses advantages of high precision and *** the remarkable superplasticity in the supercooled liquid region,amorphous alloys or metallic glasses(MGs)are regarded as ideal materials for miniature ***,due to the intrinsic metastable nature of supercooled liquids,the design of imprinting processes for MGs poses a *** the past,process parameters have largely relied on trial-and-error *** this work,a low-frequency active force modulation system is employed to apply a stable,precise,and real-time feedback stress field for imprinting of MG ***-frequency vibrations can facilitate the filling of microstructures on the template surface by reducing the effective viscosity of the supercooled *** the dataset composed of orthogonal experiments,a machine learning strategy based on back-propagation(BP)neural networks was utilized to construct a 3D parameter space for temperature,stress,and time,and to predict the corresponding filling ***,the optimal combination of imprinting process parameters was identified,and its filling ratio was experimentally validated to reach as high as *** near-perfect replication of microstructures confirms the superiority of the active force modulation system and the data-driven strategy of machine learning-assisted parameter *** the same time,this one-step microforming process provides a new approach to addressing the accuracy-cost trade-off dilemma in precision manufacturing.

关键词： metallic glass amorphous alloy microforming imprinting machine learning

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