作者:
Xu, YuanyeLiu, YuanhaoUniversity of Chinese Academy of Sciences
Key Laboratory of Networked Control System Shenyang Institute of Automation Chinese Academy of Sciences Shenyang Institute of Automation Chinese Acad. of Sci. Institutes for Robotics and Intelligent Mfg. Chinese Academy of Sciences Shenyang China
Detecting surface defects in carbon fiber-reinforced composites (FRCs) during prepreg stacking is crucial for ensuring product quality. Traditional methods using horizontal bounding boxes (HBBs) for defect detection o...
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The need for mechanical model simulation platforms is growing as a result of the ongoing advancements in digital technology and the mechanical manufacturing sector. The application scope and efficacy of simulation pla...
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Intelligent Reflecting Surface (IRS) is one of the promising technologies for improving transmission reliability of Industrial Wireless Sensor Networks (IWSNs) by creating a virtual line-of-sight (LoS) link to bypass ...
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An improved dynamic window method is proposed to solve the obstacle avoidance problem of intelligent ships in offshore waters that cannot effectively avoid when encountering unknown dynamic obstacles. Firstly, an auto...
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Transmission towers are critical infrastructure for power transmission, and the reliable operation of their equipment is essential to ensure electricity supply. However, the detection of transmission tower equipment f...
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ISBN:
(数字)9798350390315
ISBN:
(纸本)9798350390322
Transmission towers are critical infrastructure for power transmission, and the reliable operation of their equipment is essential to ensure electricity supply. However, the detection of transmission tower equipment faces challenges such as target overlap, large variations in size, small targets, and class imbalance due to the characteristics of the equipment. To tackle the identified issues, this study introduces a method based on YOLOv7 for the detection of transmission tower components, utilizing saliency-based data augmentation. Initially, an approach focusing on importance is employed to augment the sample size in categories with limited numbers, thereby enhancing the effectiveness of detection. Secondly, an adaptive adjustment module is introduced into the multi-head self-attention mechanism to dynamically adjust attention allocation based on the actual size of the targets and integrate contextual information, thus better handling targets with large size variations and overlaps. Finally, incorporating dynamic convolution within the backbone network significantly improves the ability to extract features from small objects. The outcomes of the experiments confirm the efficiency of the suggested approach in the smart surveillance of devices within intricate transmission settings, offering a reliable solution for maintaining power supply dependability.
The performance of dynamic control is intimately tied to modeling accuracy. However, traditional estimation methods and friction models, such as the least squares method and the Coulomb plus viscous model, fail to ref...
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,cha...
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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.
This paper proposes a new wireless sensor network hardware platform based on OpenWSN project launched by the University of California, Berkeley. The hardware platform's processor uses a 32-bit microcontroller (STM...
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Traditional rigid-body in-pipe robots usually have complex and heavy structures with limited flexibility and *** soft in-pipe robots have great improvements in flexibility,they still have manufacturing difficulties du...
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Traditional rigid-body in-pipe robots usually have complex and heavy structures with limited flexibility and *** soft in-pipe robots have great improvements in flexibility,they still have manufacturing difficulties due to their reliance on high-performance soft *** structure is a kind of self-stressed spatial structure consisting discrete rigid struts connected by a continuous net of tensional flexible strings,which combines the advantages of both rigid structures and soft *** applying tensegrity structures into robotics,this paper proposes a novel worm-like tensegrity robot for moving inside ***,a robot module capable of body deformation is designed based on the concept of tensegrity and its deformation performance is ***,the optimal parameters of the module are obtained based on the tensegrity *** deformation ability of the tensegrity module is tested ***,the worm-like tensegrity robot that can crawl inside pipes is developed by connecting three modules in *** performance and load capacity are tested on the prototype of the worm-like tensegrity robot by experiments of moving in horizontal pipe,vertical pipe,and elbow *** results demonstrate the effectiveness of the proposed design and suggest that the robot has high compliance,mobility,and adaptability although with simple structure and low cost.
In order to solve the issues in the heterogeneous industrial wireless network access selection such as delay and reliability, this paper present an industrial wireless network access selection based on multilevel fuzz...
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ISBN:
(数字)9798350387780
ISBN:
(纸本)9798350387797
In order to solve the issues in the heterogeneous industrial wireless network access selection such as delay and reliability, this paper present an industrial wireless network access selection based on multilevel fuzzy neural network. The algorithm divides the input attributes into three categories: network attributes, terminal attributes, and environment attributes. It synchronously inputs them into the fuzzy neural network to obtain the candidate network scores, which effectively reduces the number of fuzzy rules and reduces the algorithm complexity. Furthermore, this paper also consider the influence of the industrial environment on network selection and quantitatively reduce the number of switching and blocking rate. The simulation experimental results show that this algorithm is able to achieve fast network access selection in noisy and occluded industrial heterogeneous wireless networks, and the blocking rate can remain low in the presence of dense terminals.
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