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检索条件"任意字段=5th International Conference on Robotics and Automation Systems, Robotics 2010"

共 1354 条记录，以下是51-60 订阅

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Multi-Feature Fusion Transformer for Natural Language Inference 5

Multi-Feature Fusion Transformer for Natural Language Infere...

引用

5th international conference on robotics, Intelligent Control and Artificial Intelligence, RICAI 2023

作者： Sun, Lei Li, Xiangyang Yan, Hengxin School of Electrical Engineering and Automation Tianjin University of Technology Tianj in Key Laboratory for Control Theory and Complicated Industry Systems Tianjin China School of Electrical Engineering and Automation Tianjin University of Technology Tianjin China

ISBN: (纸本)9798350357950

Natural Language Inference (NLI) is a branch of Natural Language Processing (NLP) whose main task is to determine the relationship between two sentences. Such tasks essentially use pre-trained models to ensure accuracy, and many applications are found in human-computer dialog and question-answering systems. However, in some cases where small devices are deployed offline, lightweight model implementations are often required to save computational resources. To address this problem and ensure more efficient inference capabilities, this paper describes how to improve the preexisting Transformer and proposes a Multi-Feature Fusion Transformer Network for NLI processing. the model integrates sequence features and introduces a priori information to enhance local features. It also achieves a comprehensive fusion of sequence information, local features, and non-local features, thus compensating for many potential shortcomings of Transformer. At the same time, it maintains the lightweight feature of the model and facilitates the implementation of downstream tasks. We verified the above point by experiments, our model has better inference performance compared to previous models used for the same task. the accuracy in the SNLI dataset reached 89.0%, while the matched and mismatched versions of MultiNLI reached 79.3% and 78.7%. © 2023 IEEE.

关键词： Feature Fusion Natural language inference Natural language processing Transformer

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Research on Pipeline Climbing Gait Control of Snake Robot Based on Compound Gait 5

Research on Pipeline Climbing Gait Control of Snake Robot Ba...

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5th international conference on robotics, Intelligent Control and Artificial Intelligence, RICAI 2023

作者： Liu, Zhifan Wei, Wu Liu, Xiongding Han, Siwei School of Automation Science and Engineering South China University of Technology Guangdong Guangzhou China

ISBN: (纸本)9798350357950

To address the instability issues encountered by snake robots during climbing variable diameter pipes and curved pipes, a compound gait that combines decoupled climbing gait and serpentine gait is proposed. By utilizing sensor data to assess the climbing environment, and combining with extended Kalman filtering (EKF) for control parameter estimation, a parameter adaptive control method is designed. this method can improve the accuracy of perception environment and enhance the motion stability performance. Finally, the effectiveness of the proposed adaptive climbing gait is validated through simulation experiments. © 2023 IEEE.

关键词： climbing gait extended Kalman filtering snake robot

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Aspect-Ratio and Scale Aware Rotated Defect Detection for Fiber-reinforced Composites 5

Aspect-Ratio and Scale Aware Rotated Defect Detection for Fi...

引用

5th international conference on Computer Vision, Image and Deep Learning, CVIDL 2024

作者： Xu, Yuanye Liu, Yuanhao University 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

ISBN: (纸本)9798350373820

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 often lead to overlapping boxes and inaccurate results. this paper proposes an Aspect-Ratio and Scale Aware Detector network (ARSADet) specifically designed for rotated defect detection in FRCs. the network incorporates a Gabor convolutional network for feature extraction, an aspect-ratio and scale-aware label assignment method, and a newly established FRCs Oriented Defect Detection dataset (FODD). Evaluation on the FODD dataset demonstrates superior performance compared to existing methods. © 2024 IEEE.

关键词： Aspect ratio

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Hyper-parameter Optimization in the context of Smart Manufacturing: a Systematic Literature Review 5

Hyper-parameter Optimization in the context of Smart Manufac...

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5th international conference on Industry 4.0 and Smart Manufacturing (ISM)

作者： Chernigovskaya, Maria Nahhas, Abdulrahman Kharitonov, Andrey Turowski, Klaus Otto von Guericke Univ Magdeburg Res & Competence Cluster Very Large Bus Fac Comp Sci Univ Pl 2 D-39106 Magdeburg Germany

Smart manufacturing involves the use of a variety of automation solutions, such as robotics, machines with embedded software, and advanced sensors collecting vast quantities of data. Efficient control of a complex composition of such solutions, as well as the analysis of the collected data, are essential for improving the efficiency of the production processes and decision-making. Data analysis and process optimization are enabled through the application of state-of-the-art optimization and machine learning algorithms. However, the efficient use of these algorithms often depends on the careful selection of the parameters, which on its own is a process that requires a high degree of expertise and time. therefore, another class of algorithms can be applied that is designed to discover the optimal parameter configuration given the specific nature of the manufacturing process and the used algorithm. In this work, we systematically analyze the published literature to discover which parameter selection techniques are used in the context of Industry 4.0, for which processes, and how these benefit from automated parameter selection. Within our literature review, we discover nine relevant publications, most of which concentrate on parameter selection for machine learning algorithms through various numerical optimization and metaheuristic techniques. (C) 2024 the Authors. Published by Elsevier B.V.

关键词： Hyper-parameters optimization Smart Manufacturing Industry 4.0 automation

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Magnetically Assembled Electronic Digital Materials 5

Magnetically Assembled Electronic Digital Materials

引用

5th international conference on Manipulation, automation, and robotics at Small Scales (MARSS)

作者： Lapunik, Vojtech Jurik, Martin Vitek, Martin Kuthan, Jiri Mach, Frantisek Univ West Bohemia Pilsen Fac Elect Engn Plzen Czech Republic

ISBN: (数字)9781665459730

ISBN: (纸本)9781665459730

the concept of digital materials at the boundary of electric circuits and miniature robotics is studied. the main objective is to develop an experimental framework for the automatic assembly of basic electric circuits from the elementary modules. the framework is demonstrated on tiny modules, so-called bits, which take advantage of magnetic actuation and connection, both electrically and mechanically. the concept has potential application in small-scale robotics, especially for modular reconfigurable and versatile insect-scale robots, which can be used as elementary parts of complex reconfigurable machines.

关键词： Integer programming Fabrication Couplings Electric potential automation Genetics Robots

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Optical Character Recognition of Medical Records Based on Deep Learning 5

Optical Character Recognition of Medical Records Based on De...

引用

5th international conference on robotics and Computer Vision, ICRCV 2023

作者： Jing, Wanting Liu, Ziyi Zhang, Shuoshuo Yin, Yunru Chen, Congyan School of Automation Southeast University Nanjing China School of Electrical Engineering Southeast University Nanjing China

ISBN: (纸本)9798350326369

Retrieving the medical records of the insured is a crucial step in the insurance company's claim investigation and helps to prevent insurance fraud. Due to the huge workload and sometimes even additional expenses incurred by entrusting a third party, it's necessary to develop a medical record processor, which can automatically recognize medical records. Optical character recognition (OCR) has been a hot research topic in recent years owing to its outstanding ability to transmute scanned images and other visuals into text. A deep-learning-based OCR software was developed for the detection and recognition of medical records recognition and automatic calibration of medical records OCR in both Chinese and English are studied and realized, including classifying the physical drawings and scanned copies and removing the seal on the medical record sheet of scanned ones. Based on the observations from the analysis we give several suggestions related to the design and implementation of medical record processing approaches. © 2023 IEEE.

关键词： Deep learning

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Non-Singular Terminal Sliding Mode Control Based on Finite-Time Extended State Observer for Robotic systems 5

Non-Singular Terminal Sliding Mode Control Based on Finite-T...

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5th international conference on robotics, Intelligent Control and Artificial Intelligence, RICAI 2023

作者： Dai, Gengwei Zhufu, Guanfeng Wang, Shubo College of Automation Qingdao University Qingdao China

ISBN: (纸本)9798350357950

During the control process of robotic system, problems such as slow speed and low accuracy in trajectory tracking control caused by external disturbance and internal parameter uncertainties always happen. Aiming at the above problems, an improved finite-time extend state observer (FTESO) based non-singular fast terminal sliding mode control (NFTSMC) with funnel boundary constraints is proposed in this paper. Firstly, a FTESO with special feedback mechanism, is designed to estimate both the unmeasured states and lumped uncertainties. In addition, by incorporating the error transformation into the sliding mode surface, a novel finite time controller is designed to improve the anti-interference ability and dynamic performance. In order to confirm the superiority of the suggested control strategy, varies comparison simulations are conducted at the end. © 2023 IEEE.

关键词： finite-time extended state observer funnel robotic system sliding mode control trajectory tracking

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Trajectory Tracking Method for Wheel-Leg Climbing Robot on Complex Facade 5

Trajectory Tracking Method for Wheel-Leg Climbing Robot on C...

引用

5th international conference on robotics, Intelligent Control and Artificial Intelligence, RICAI 2023

作者： Zhao, Jinpeng Jiangsu Automation Research Institute Ministry of Science and Technology Jiangsu China

ISBN: (纸本)9798350357950

Maintenance operations on large metal facades, such as petrochemical storage tanks and civilian ships, are crucial for ensuring their safe operation. Traditional manual methods are plagued by poor safety, low operational efficiency, and significant resource wastage. thus, this study investigates the motion mechanics and trajectory tracking control methods for maintenance robot systems on metal facades, resulting in the development of a high-performance and adaptive wheeled-legged magnetic adhesion climbing robot prototype. Utilizing the principles of virtual kinematics and degrees of freedom theory, the study extracts multidimensional constraints and independent coordinate variables to establish a coupled disturbance kinematic model for the robot. To address pose errors caused by uncertainties in body parameters and external disturbances during operations, an adaptive extended observer and sliding mode torque controller are proposed, introducing an adaptive extended observer sliding mode control method for trajectory tracking. Lyapunov theory is employed to demonstrate the stability and convergence of the designed controllers. through simulation experiments, the effectiveness and superiority of the proposed trajectory tracking control method are substantiated. © 2023 IEEE.

关键词： climbing robot motion control trajectory tracking wheeled-legged magnetic adhesion

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Autonomous Mobile Medical Robot Based on SLAM Algorithm 5

Autonomous Mobile Medical Robot Based on SLAM Algorithm

引用

5th international conference on Advances in Electrical Engineering and Computer Applications, AEECA 2024

作者： Yao, Xinyi Shanghai Maritime University College of Transport & Communications Shanghai China

ISBN: (纸本)9798350355253

this paper aims to develop an autonomous navigation medical robot suitable for indoor medical environments, equipped with a Mecanum wheel AGV platform and the Hector-SLAM algorithm for accurate localization and map building. the robot uses laser radar and vision systems for environmental perception, and employs the A∗ algorithm and the Dynamic Window Approach (DWA) for path planning and obstacle avoidance. Experimental results show that Hector-SLAM outperforms traditional methods in terms of accuracy and adaptability, effectively enhancing the level of automation in medical settings. the research confirms that the medical robot's navigation system has significant application potential in complex indoor environments, offering a new direction for future medical rescue. © 2024 IEEE.

关键词： Medical robotics

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Research on Trajectory Planning of Orchard Robot 5

Research on Trajectory Planning of Orchard Robot

引用

5th international conference on robotics, Intelligent Control and Artificial Intelligence, RICAI 2023

作者： Miao, Zhonghua Lu, Hao Li, Nan Wang, Dong School of Mechatronics Engineering and Automation Shanghai University Shanghai China

ISBN: (纸本)9798350357950

In contrast to typical scenarios, orchards present a more intricate environment characterized by numerous irregular obstructions. this complexity often leads to the generation of zigzag paths when employing conventional path planning algorithms. Moreover, the challenge is compounded by the orchard's slippery terrain and the fact that traditional path planning approaches do not consider robot kinematics, necessitating abrupt changes in acceleration. Such conditions make it arduous for orchard robots to follow these paths effectively. To mitigate these issues, this study introduces the minimum Jerk principle, which focuses on minimizing the rate of change in robot acceleration, as the cost function for optimizing the paths devised by standard path planning methods. the paper culminates in an empirical evaluation using a robot in an orchard setting. Experimental results demonstrate a substantial reduction in the robot's angular velocity fluctuations and a 12% decrease in tracking time, compared to paths generated by conventional methods. © 2023 IEEE.

关键词： orchard robot path planning trajectory optimization

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