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检索条件"任意字段=2024 International Conference on Intelligent Robotics and Automatic Control"

共 5263 条记录，以下是521-530 订阅

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2024 8th international conference on robotics, control and Automation, ICRCA 2024

2024 8th International Conference on Robotics, Control and A...

引用

8th international conference on robotics, control and Automation, ICRCA 2024

ISBN: (纸本)9798350344721

The proceedings contain 85 papers. The topics discussed include: a hybrid method for INS/GPS integrated navigation system based on the improved Karman filter and back propagation neural network;development of Simulink-based physical experiment platform for EtherCAT bipedal robots;a biogeography-based optimization algorithm with heuristics for distributed multiproduct scheduling problem;research on low energy consumption AC system control strategy of battery electric vehicles;flyback converter modeling and overload control characteristics for power supply based on state space averaging;a simple confidence-supervised model for high resolution defect recognition;research and development of intelligent warehouse management system based on RFID technology;research on methods of vehicle image retrieval in expressway scenarios based on deep learning neural network;and motion simulation control system of detecting robot based on digital twin.

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Design of Wind Turbine Cabin Inspection Robot System 7

Design of Wind Turbine Cabin Inspection Robot System

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7th international conference on intelligent robotics and control Engineering, IRCE 2024

作者： Shen, Lu Zhao, Xinyi Gao, Chen Shen, Runjie Tongji University College of Electronic and Information Engineering Shanghai China Wudongde Power Plant of China Yangtze Power Co. Ltd. Kunming China Tongji University Sino-German Center of Intelligent Systems College of Electronic and Information Engineering Shanghai China

ISBN: (纸本)9798350352399

This paper designs a wind turbine cabin inspection robot system, which comprises three components: the robot body, the communication system, and the monitoring software. The robot body features an elliptical track and houses various sensors, including a visible light camera, an infrared camera, and a microphone. These sensors are used to capture real-time images, video, and sound data from inside the wind turbine cabin. The communication system enables the transmission of data and commands between the robot and the monitoring software. Inspection staff can remotely observe the internal conditions of the wind turbine cabin and control the robot's movements through the monitoring software, thus eliminating the need for on-site inspections. This intelligent and automated inspection method aligns with the future direction of industry development. © 2024 IEEE.

关键词： Wind turbines

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Research on automatic cigarette appearance defect detection system based on deep learning algorithm 7

Research on automatic cigarette appearance defect detection ...

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7th international conference on Automation Electronics and Electrical Engineering

作者： Wang, Bao Bi, Sheng Gansu Tobacco Ind Co Ltd Lanzhou Gansu Peoples R China

ISBN: (纸本)9798350377040;9798350377033

In this paper, an automatic cigarette appearance defect detection system based on deep learning algorithm is proposed, aiming to improve the defect detection efficiency and accuracy in the cigarette production process. By using a pre-trained ResNet18 network model, the system automatically identifies defective products in the cigarette production line. We trained and validated the model on the dataset, and showed the trends of the loss function and accuracy during the training process. The experimental results show that the model can effectively recognize multiple cigarette defects, especially in handling broken and deformed defects, and exhibits high accuracy and robustness. The study shows that the application of deep learning-based defect detection technology in cigarette production has significant potential and can provide intelligent solutions for quality control.

关键词： Deep Learning Cigarette Defect Detection ResNet18 automatic Recognition Quality control

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Language-driven Grasp Detection with Mask-guided Attention

Language-driven Grasp Detection with Mask-guided Attention

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2024 international conference on intelligent Robots and Systems

作者： Nan Van Vo Minh Nhat Vu Huang, Baoru An Vuong Ngan Le Thieu Vo Anh Nguyen FPT Software AI Ctr Hanoi Vietnam TU Wien Automat & Control Inst Vienna Austria Austrian Inst Technol AIT GmbH Vienna Austria Imperial Coll London London England Univ Arkansas Dept Comp Sci & Comp Engn Fayetteville AR 72701 USA Natl Univ Singapore Singapore Singapore Univ Liverpool Dept Comp Sci Liverpool Merseyside England

ISBN: (纸本)9798350377712;9798350377705

Grasp detection is an essential task in robotics with various industrial applications. However, traditional methods often struggle with occlusions and do not utilize language for grasping. Incorporating natural language into grasp detection remains a challenging task and largely unexplored. To address this gap, we propose a new method for language-driven grasp detection with mask-guided attention by utilizing the transformer attention mechanism with semantic segmentation features. Our approach integrates visual data, segmentation mask features, and natural language instructions, significantly improving grasp detection accuracy. Our work introduces a new framework for language-driven grasp detection, paving the way for language-driven robotic applications. Intensive experiments show that our method outperforms other recent baselines by a clear margin, with a 10.0% success score improvement. We further validate our method in real-world robotic experiments, confirming the effectiveness of our approach.

关键词： Semantics

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Plant-Wide Process Incipient Fault Detection via Double-Layer Subspace Weighted Moving Window Reconstruction ICA 11

Plant-Wide Process Incipient Fault Detection via Double-Laye...

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11th IEEE international conference on Cybernetics and intelligent Systems (CIS) / 11th IEEE international conference on robotics, Automation and Mechatronics (RAM)

作者： Song, Bing Song, YiMeng Shi, Hongbo Jiang, QingChao East China Univ Sci & Technol Key Lab Adv Control & Optimizat Chem Proc Minist Educ Shanghai Peoples R China

ISBN: (纸本)9798350364200;9798350364194

With the widespread use of distributed systems, multi-subspace whole-flow industrial monitoring methods are evolving. However, due to the lack of distinctive features, incipient faults in plant-wide processes are more difficult to detect. To improve the detection rate of incipient faults in plant-wide processes while maintaining the generality of the algorithm, a novel double-layer subspace weighted moving window reconstruction independent component analysis (DS-WRICA) method is proposed. In DS-WRICA, process variables are first divided into different subspaces based on process knowledge and data-driven partitioning methods. Secondly, a weighted moving window is used to increase the offset of incipient faults, and monitoring statistics are constructed by combining optimized reconstructed independent component analysis (RICA) and local outlier factor (LOF) in each subspace. Then, the monitoring statistics in each subspace are fused with information by Bayesian inference fusion method to obtain distributed monitoring results. Finally, the effectiveness and superiority of the DS-WRICA method are verified by industrial examples.

关键词： Data driven plant-wide process incipient fault detection distributed system weighted moving window reconstructed independent component analysis

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Comparative Study of Q-Learning and SARSA Algorithms for UAV Path Planning in 3D Environments 28

Comparative Study of Q-Learning and SARSA Algorithms for UAV...

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28th IEEE international conference on intelligent Engineering Systems (INES)

作者： Zaghbani, Imen Jarray, Raja Bouallegue, Soufiene Univ Tunis El Manar Natl Engn Sch Tunis Res Lab Automat Control LARA Tunis 1002 Tunisia Univ Gabes Res Lab Automat Control LARA Natl Engn Sch Tunis Tunis 1002 Tunisia Univ Gabes High Inst Ind Syst Gabes Tunis 6072 Tunisia

ISBN: (纸本)9798350367607;9798350367591

Path planning processes in 3D environments with obstacles are essential for ensuring the successful navigation of Unmanned Aerial Vehicles (UAVs). Recently, the artificial intelligence theory presents increasingly effective algorithms and tools to address such a robotics challenge. This paper presents a comparative study of two most commonly used Reinforcement Learning (RL) algorithms, namely Q-learning and SARSA learning. Through numerical experimentations under different navigation scenarios with varying levels of complexity and increasing numbers of static obstacles, key performance metrics like path's length, total actions number, average reward, execution time and collision avoidance are considered and evaluated. The demonstrative results indicate that the Q-learning algorithm well addressed the challenges of UAVs' path planning in static environments. The performance of such an algorithm has proven to be satisfactory and more promising for UAVs' navigation in complex configuration spaces when compared to the SARSA algorithm.

关键词： Unmanned aerial vehicles path planning reinforcement learning Q-learning SARSA learning

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PGFLP 1.0: Benchmark Suite and Dataset for automatic License Plate Recognition in the wild 10

PGFLP 1.0: Benchmark Suite and Dataset for Automatic License...

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10th international conference on control, Decision and Information Technologies (CoDIT)

作者： Ismail, Amir Mehri, Maroua Sahbani, Anis Ben Amara, Najoua Essoukri Univ Sousse LATIS Lab Adv Technol & Intelligent Syst Ecole Natl Ingn Sousse Sousse 4023 Tunisia Enova Robot SA Technopole Sousse Sousse 4000 Tunisia Sorbonne Univ Inst Intelligent Syst & Robot ISIR CNRS Paris France

ISBN: (纸本)9798350373981;9798350373974

automatic license plate recognition (ALPR) is a powerful tool for analyzing the growing number of vehicles in major cities worldwide. However, building datasets that accurately represent vehicles and license plates (LPs) is challenging, as most current datasets are specific to certain countries and do not provide a comprehensive representation. This remains particularly true for French LPs, where there is currently no publicly available dataset that covers a wide range of scenarios such as plate inclinations, varying lighting conditions, and changing weather. To address this issue, we present a benchmark suite called PGFLP 1.0, which includes more than 14k fully annotated LPs from several vehicle categories (e.g. cars, trucks, motorcycles). PGFLP 1.0 includes three annotation levels: rectangular boxes for the LP, four vertices of the LP region, and labels for the full LP sequence. Using PGFLP 1.0, we provide an experimental evaluation of the most recent ALPR approaches, assessing their ability to detect and recognize LPs. This work provides a useful benchmark in terms of accuracy and speed for current and future research efforts in ALPR.

关键词： Benchmark annotated dataset French license plates in-the-wild mobile robot detection recognition

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Motion control for Continuum Robots: A Mini Review for Model-Free and Hybrid-Model control 17th

Motion Control for Continuum Robots: A Mini Review for Model...

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17th international conference on intelligent robotics and Applications

作者： Du, Zupeng Yang, Laihao Sun, Yu Chen, Xuefeng Xi An Jiao Tong Univ Sch Mech Engn Xian Peoples R China

ISBN: (纸本)9789819607792;9789819607808

Continuum robots with soft, deformable and multi-degree-of-freedom features can adapt to complex environments and perform tasks flexibly, therefore, gradually reflecting important application values in minimally invasive surgery, deep cavity exploration and other fields. To enable continuum robots to perform tasks dexterously and adaptively in complex environments, their motion control is crucial. Traditional model-based control methods require accurate system modelling, have high environmental and structural requirements, and face real-time and computational complexity challenges. With the continuous development of robotics, model-free control and hybrid-model control have become two important approaches to solve the motion control problems of continuum robots. This review systematically summarizes the current status of research on model-free and hybrid-model control for continuum robots in recent years, and discusses in depth the advantages and disadvantages as well as the challenges of the various methods, so as to provide guidance for the coming followers, and to promote the further development and application of continuum robots.

关键词： Continuum robot Model-free control Hybrid-model control

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A mortar scraping robot for a whole wall in construction 21

A mortar scraping robot for a whole wall in construction

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21st IEEE international conference on Mechatronics and Automation (IEEE ICMA)

作者： Liu, Guocai Li, Zebin Zhang, Jinsi Bao, Huifang West Anhui Univ Dept Elect & Optoelect Engn Coll Luan Anhui Peoples R China

ISBN: (纸本)9798350388084;9798350388077

One of the challenging research issues in building construction is using robot for reducing people's labor intensity. This paper develops a cement mortar scraping robot which can scrape a whole wall in one time without operator invention. In this paper, the mechanical and electrical structure of the robot is described, and the algorithm of the omnidirectional movement algorithm is given. The robot is tested in construction site, and the result shows that it can reduce people's labor intensity and improve work efficiency significantly.

关键词： construction robot scraping robot intelligent construction

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2024 4th international conference on Computer, control and robotics, ICCCR 2024

2024 4th International Conference on Computer, Control and R...

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4th international conference on Computer, control and robotics, ICCCR 2024

ISBN: (纸本)9798350373141

The proceedings contain 70 papers. The topics discussed include: Frustum PointVoxel-RCNN: a high-performance framework for accurate 3D object detection in point clouds and images;design of intelligent pet drying system based on OpenMv;a multimodal knowledge representation method for fake news detection;computer and vision aided mapping in farmer's market and visually aided shopping strategy for visually impaired individuals;knowledge exploring on the medication regularity of the infectious fever treatment in Wai Tai Mi Yao based on cluster analysis and association rules;comparative analysis of deep learning-based defect monitoring in metal additive manufacturing;simulation analysis of two-phase flow field in robotic sand blasting with aluminum alloy car body;and a reinforcement learning driven iterated greedy algorithm for energy-efficiency flexible job-shop scheduling problem.

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