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Green innovation unleashed:Harnessing tungsten-based nanomaterials for catalyzing solar-driven carbon dioxide conversion

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Chinese Chemical Letters 2025年第2期36卷 108-117页

作者： Weidan Meng Yanbo Zhou Yi Zhou State Environmental Protection Key Laboratory of Environmental Risk Assessment and Control on Chemical Process East China University of Science and TechnologyShanghai 200237China National Engineering Research Center of Industrial Wastewater Detoxication and Resource Recovery East China University of Science and TechnologyShanghai 200237China Shanghai Engineering Research Center for Multi-media Environmental Catalysis and Resource Utilization East China University of Science and TechnologyShanghai 200237China Shanghai Institute of Pollution Control and Ecological Security Shanghai 200092China

Carbon dioxide photocatalytic reduction (CO_(2)-PR) is an efficient method for controlling CO_(2)emissions and generating cleaner energy while mitigating global *** oxides (WxOy) have attracted considerable attention for CO_(2)-PR due to their excellent spectral ***,comprehensive reviews are lacking on the use of WxOyfor CO_(2)-***,this review provides a detailed summary of t research progress made with WxOy-based catalysts in CO_(2)-*** also explains the fundamental principles of CO_(2)-PR and evaluates key performance indicators that affect the activity of WxOy-based photocatalysts,including yield,selectivity,stability,and apparent quantum ***,this review explores opportunities for synthesizing high-performance WxOy-based photocatalysts and highlights their potential for the green preparation of C1/C2 products through CO_(2)-*** innovative strategies aim to address the challenges and pressures associated with energy and environmental issues,particularly by enhancing artificial photosynthesis efficiency.

关键词： Carbon dioxide photoreduction Tungsten-based nanocatalyst Mechanism Performance evaluation Selectivity

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A Survey on Design,Actuation,Modeling,and control of Continuum Robot

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Cyborg and Bionic systems 2022年第1期2022卷 22-34页

作者： Jingyu Zhang Qin Fang Pingyu Xiang Danying Sun Yanan Xue Rui Jin Ke Qiu Rong Xiong Yue Wang Haojian Lu State Key Laboratory of Industrial Control and Technology Zhejiang UniversityHangzhou 310027China Institute of CyberSystems and Control The Department of Control Science and Engineering Zhejiang UniversityHangzhou 310027China Department of Plastic Surgery Sir Run Run Shaw HospitalZhejang University of MedicineHangzhou 310016China

Inthis paper,we describethe advances inthe design,actuation,modeling,and controlfield of continuum *** decades ofpioneering research,many innovativeve structural designandUntethered magnetic robots are agood example;its external actuationcharteristigotten a lot of interest ***,modeling approachesbased on continuunnechals after years oof *** when combined withnumerical analytic methodschtFifecodle-b *** the control,*** and hybrid control methodscombined with sensor *** the other hand,tladeg and control of continum *** data-driven modeling technique simplifies modeling aproves anti-interference and generalization *** paper discusses the current development and challenges of continum robots in the above felds and provides prospectsfor the future.

关键词： Robot modeling generalization

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Fabrication of helical flutes on the micro-drill surface by micro-EDM using composite disc foil electrodes

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International Journal of Advanced Manufacturing technology 2025年第5期138卷 2357-2367页

作者： Xu, Bin Liu, Weitong Lian, Manqun Lei, Jianguo Wu, Xiaoyu Fu, Lianyu Zhao, Chunyang Zhang, Canbin Guangdong Provincial Key Laboratory of Micro/Nano Optomechatronics Engineering College of Mechatronics and Control Engineering Shenzhen University Guangdong Shenzhen518060 China Shenzhen Jinzhou Precision Technology Corp Shenzhen518116 China State Key Laboratory of Ultra-Precision Machining Technology Department of Industrial and Systems Engineering The Hong Kong Polytechnic University Hung Hom Kowloon Hong Kong

Micro-drills are widely used in the micro-hole machining of printed circuit boards. Helical flutes, the core feature of micro-drills, play a crucial role in chip discharge. Precision grinding technology is commonly used for machining the helical flutes in micro-drills. Grinding is a contact machining technology that generates a grinding force during the process. When the diameter of the micro-drill is minimal (Φ ≤ 100 µm), the grinding force is extremely prone to cause deformation or even fracture of the micro-drill, leading to a decreased yield. To overcome the above problem, the paper proposed an approach to fabricate a helical flute structure on the surface of a micro-drill by micro electrical discharge machining (micro-EDM) using a beryllium-copper-tin composite disc foil electrode (CDFE). Micro-EDM, a type of non-contact machining, can effectively avoid the disadvantage of grinding the helical flute of the micro-drill. Through an orthogonal experiment, the effects of the rotation velocity of the CDFE, machining voltage, and pulse duration ratio on the machining quality of the helical flutes were analysed in detail. Finally, with 4000 r/min CDFE rotation velocity, 24 V machining voltage, 1 µs pulse duration and 3 µs pulse interval, a helical flute structure with a surface roughness Ra of 0.381 µm was successfully machined on the surface of a 70 µm diameter micro-drill. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2025.

关键词： Surface roughness

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BEV2PR: BEV-Enhanced Visual Place Recognition with Structural Cues

BEV2PR: BEV-Enhanced Visual Place Recognition with Structura...

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IEEE/RSJ International Conference on Intelligent Robots and systems (IROS)

作者： Fudong Ge Yiwei Zhang Shuhan Shen Weiming Hu Yue Wang Jin Gao State Key Laboratory of Multimodal Artificial Intelligence Systems (MAIS) CASIA School of Artificial Intelligence University of Chinese Academy of Sciences School of Information Science and Technology ShanghaiTech University State Key Laboratory of Industrial Control Technology and Institute of Cyber-Systems and Control Zhejiang University

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

In this paper, we propose a new image-based visual place recognition (VPR) framework by exploiting the structural cues in bird’s-eye view (BEV) from a single monocular camera. The motivation arises from two key observations about place recognition methods based on both appearance and structure: 1) For the methods relying on LiDAR sensors, the integration of LiDAR in robotic systems has led to increased expenses, while the alignment of data between different sensors is also a major challenge. 2) Other image-/camera-based methods, involving integrating RGB images and their derived variants (e.g., pseudo depth images, pseudo 3D point clouds), exhibit several limitations, such as the failure to effectively exploit the explicit spatial relationships between different objects. To tackle the above issues, we design a new BEV-enhanced VPR framework, namely BEV 2 PR, generating a composite descriptor with both visual cues and spatial awareness based on a single camera. The key points lie in: 1) We use BEV features as an explicit source of structural knowledge in constructing global features. 2) The lower layers of the pretrained backbone from BEV generation are shared for visual and structural streams in VPR, facilitating the learning of fine-grained local features in the visual stream. 3) The complementary visual and structural features can jointly enhance VPR performance. Our BEV 2 PR framework enables consistent performance improvements over several popular aggregation modules for RGB global features. The experiments on our collected VPR-NuScenes dataset demonstrate an absolute gain of 2.47% on Recall@1 for the strong Conv-AP baseline to achieve the best performance in our setting, and notably, a 18.06% gain on the hard set. The code and dataset will be available at https://***/FudongGe/BEV2PR.

关键词： Image sensors Visualization Laser radar Three-dimensional displays Robot vision systems Cameras Sensor systems Sensors Streams Visual place recognition

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Implicit Scene Context-aware Interactive Trajectory Prediction for Autonomous Driving

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on Intelligent Vehicles 2023年第9期9卷 1-17页

作者： Lan, Wenxing Li, Dachuan Hao, Qi Zhao, Dezong Tian, Bin Research Institute of Trustworthy Autonomous Systems Southern University of Science and Technology Shenzhen China James Watt School of Engineering University of Glasgow Glasgow U.K State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences China

The accurate prediction of behaviors of surrounding traffic participants is critical for autonomous vehicles (AV). How to fully encode both explicit (e.g., map structure and road geometry) and implicit scene context information (e.g., traffic rules) within complex scenarios is still challenging. In this work, we propose an implicit scene context-aware trajectory prediction framework (the PRISC-Net, Prediction with Implicit Scene Context) for accurate and interactive behavior forecasting. The novelty of the proposed approach includes: 1) development of a behavior prediction framework that takes advantage of both model- and learning-based approaches to fully encode scene context information while modeling complex interactions;2) development of a candidate path target predictor that utilizes explicit and implicit scene context information for candidate path target prediction, along with a motion planning-based generator that generates kinematic feasible candidate trajectories;3) integration of the proposed target predictor and trajectory generator with a learning-based evaluator to capture complex agent-agent and agent-scene interactions and output accurate predictions. Experiment results based on vehicle behavior datasets and real-world road tests show that the proposed approaches outperform state-of-the-art methods in terms of prediction accuracy and scene context compliance. IEEE

关键词： Trajectories

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PCEB-YOLOV8: An Improved PCB Defect Detection Method Based on YOLOV8 8

PCEB-YOLOV8: An Improved PCB Defect Detection Method Based o...

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8th International Conference on Electrical, Mechanical and Computer Engineering, ICEMCE 2024

作者： Li, Meihui Song, Chunhe Yu, Xia Chu, Mengmeng Li, Rui Shenyang University of Technology State Key Laboratory of Robotics 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 Shenyang Shenyang China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Key Laboratory of Networked Control Systems Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang Shenyang China Shenyang University of Technology Shenyang China

ISBN: (纸本)9798331506230

Printed circuit board defect recognition is of great significance to ensuring the quality of electronic products. This paper proposes an improved PCB defect detection method based on YOLOV8. Firstly, the data augmentation method PredMix (prediction mix) is adopted to simulate scenarios such as overlapping and occlusion in images, where the displays are incomplete or blurred, thereby enhancing the robustness of the network model. Secondly, BiFPN is used to replace PAN-FPN in the fusion layer to strengthen the feature fusion capability. Finally, the CESE_C2f module is employed in the Backbone part, leveraging a lightweight attention mechanism to improve the detection effect while reducing the number of parameters. Experimental results show that compared with the original YOLOV8, the MAP value of this improved algorithm reaches 92.6%, with a 2.3% increase in accuracy. © 2024 IEEE.

关键词： Deep learning

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A Comprehensive Review of Humanoid Robots

SmartBot

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SmartBot 2025年第1期1卷 86-120页

作者： Qincheng Sheng Zhongxiang Zhou Jinhao Li Xiangyu Mi Pingyu Xiang Zhenghan Chen Haocheng Xu Shenhan Jia Xiyang Wu Yuxiang Cui Shuhao Ye Jiyu Yu Yuhan Du Shichao Zhai Kechun Xu Yifei Yang Zhichen Lou Zherui Song Zikang Yin Yu Sun Rong Xiong Jun Zou Huayong Yang State Key Laboratory of Fluid Power and Mechatronic Systems School of Mechanical EngineeringZhejiang UniversityHangzhouChina State Key Laboratory of Industrial Control Technology School of Control Science and EngineeringZhejiang UniversityHangzhouChina

Humanoid robots,increasingly recognized for their potential to drive economic and social development,have garnered significant attention in recent *** paper aims to provide a comprehensive overview of the progress,challenges,and future directions in humanoid robotics,with a particular emphasis on essential system components and key technological *** a review of historical milestones,this paper explores critical aspects such as the design of the head and body,and examines state-of-the-art technologies in areas like locomotion control,perception,and intelligent *** presenting a thorough analysis of the field,this work aims to serve as a valuable resource for researchers and inspire future innovations that will drive the continued evolution of humanoid robots.

关键词： challenges and trends humanoid robot humanoid robot components key technologies

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Ultrasonic enhancement of persulfate oxidation system governs emerging pollutants decontamination

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Green Energy & Environment 2024年第11期9卷 1666-1678页

作者： Yanpan Li Yanbo Zhou Yi Zhou National Engineering Research Center of Industrial Wastewater Detoxication and Resource Recovery State Environmental Protection Key Laboratory of Environmental Risk Assessment and Control on Chemical ProcessEast China University of Science and Technology130 Meilong RoadShanghai200237China Shanghai Engineering Research Center for Multi-media Environmental Catalysis and Resource Utilization East China University of Science and Technology130 Meilong RoadShanghai200237China Shanghai Institute of Pollution Control and Ecological Security Shanghai200092China

Emerging contaminants (ECs) are widely present in aquatic environments, posing potential risks to both ecosystems and human health. Theultrasound-assisted persulfate oxidation process has attracted considerable attention in the degradation of ECs due to its ability to generate bothsulfate radicals and cavitation effects, enhancing degradation effects. In this paper, the principle of ultrasonic synergistic Fenton-like oxidationsystem for degrading organic pollutants was reviewed, divided into homogeneous system, non-homogeneous system, and single-atom system toexplore the synergistic effect of ultrasound-enhanced persulfate technology in three aspects, and the effects of environmental factors such asultrasonic frequency and power, system pH, temperature, and initial oxidant concentration on the system's decontamination performance werediscussed. Finally, future research on ultrasonically activated persulfate technology is summarized and prospected.

关键词： Ultrasound Persulfate Emerging contaminants Reaction mechanism Synergistic effects

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Disturbance Observer-based Model Predictive control for Discrete-time Linear systems with Bounded Disturbances 41

Disturbance Observer-based Model Predictive Control for Disc...

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第41届中国控制会议

作者： Mengzhi Wang Bing Liu Jichao Bi Kaixiang Yang Jingpei Wang Nanwei Yao State Key Laboratory of Industrial Control Technology Zhejiang University Zhejiang Institute of Industry and Information Technology China Academy of Information and Communications Technology

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

This work develops a disturbance rejection model predictive control(MPC) algorithm for discrete-time linear systems with bounded disturbances.A disturbance observer is designed to estimate the unknown matched disturbances with bounded incremental constraint.A tube-based MPC algorithm is presented to handle the system constraints.A composite controller is presented to stabilize the systems,including a MPC controller to drive the system state into the neighborhood of the origin,and a disturbance estimation-dependent controller to compensate for the effect of external *** feasibility of the disturbance rejection MPC is analyzed,and the stability of the system can be *** results show the effectiveness of the proposed methods.

关键词： Model predictive control Disturbance observer Bounded disturbances

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Analysis of LoRa for Electronic Shelf Labels Based on Distributed Machine Learning 42

Analysis of LoRa for Electronic Shelf Labels Based on Distri...

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42nd Chinese control Conference, CCC 2023

作者： Khan, Malak Abid Ali Ma, Hongbin Jin, Ying Ma, Jingxiang Rehman, Zia Ur Rahman, Mizanur School of Automation Beijing Institute of Technology Beijing100081 China Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing100081 China

ISBN: (纸本)9789887581543

Deforestation is the primary source of global warming;traditional shelf labels use paper to display the price of the products, and human forces play a pivotal role in updating the tags where the pandemic has strictly limited its power. Various technologies provide connectivity and a fast-updating system to eliminate the paper-based approach. LoRa is one of the contenders to design the system for electronic shelf labels (ESLs). In this paper, LoRa has been used to minify data losses and guarantee the successful decoding of the carrier signals. The data parallelism at the network server (NS) is used to distribute the data packets among the gateways (GWs) for concurrent transmissions to the end devices (EDs). The EDs are placed in different ranges using machine clustering to avoid intra-SF interference and collision. The data rate (DR) and spreading factors (SFs) have been proposed to improve the performance of pure and slotted ALOHA for the properly allocated tags. The orthogonality principles follow industrial, scientific, and medical regulations (ISM) to avoid data traffic congestion. GWs under different duty cycles (DC) and bandwidth (BW) are examined to minify the network saturation and reduce the energy harvesting of the tags. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Deforestation

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