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检索条件"任意字段=International Conference on Advances in Science, Engineering and Robotics Technology"

共 48226 条记录，以下是1531-1540 订阅

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Research on Aircraft Automatic Drilling and Riveting Task Planning and Simulation technology Based on DELMIA 3

Research on Aircraft Automatic Drilling and Riveting Task Pl...

引用

3rd international conference on Automation, robotics and Computer engineering, ICARCE 2024

作者： Jin, Tao Lin, Chenyang Shi, Jiancheng Southwest China Research Institute of Electronic Equipment Craft Department Chengdu China

ISBN: (纸本)9798331529505

Based on the application content, scope, and process of digital enterprise lean manufacturing interactive application (DELMIA), conduct research on aircraft automatic drilling and riveting task planning and simulation technology. Establish a process numerical model for the product, study the optimal path planning for the assembly process, achieve automatic planning of robot drilling and riveting tasks, and generate numerical control (NC) code for robot execution. Virtual simulation of robot automatic drilling and riveting tasks based on DELMIA, conducting assembly interference inspection, and achieving advance planning and simulation of production assembly tasks. Verify the effectiveness and accuracy of automatic drilling and riveting task planning and simulation methods through examples. The results indicate that the hole position error after processing is controlled within 0.3mm, which can meet the requirements of hole making. © 2024 IEEE.

关键词： automatic drilling and riveting DELMIA off-line programming robot virtual simulation

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A comprehensive review of recent advances and challenges in artificial intelligence and machine learning 4th

A comprehensive review of recent advances and challenges in ...

引用

4th international conference on Computational Methods in science and technology, ICCMST 2024

作者： Singla, Ishdeep Hans, Aarti Smiksha Diya Swami, Harsh Kumar Ranjan, Rahul Computer Science and Engineering Chandigarh University Mohali Gharuan India

ISBN: (纸本)9781032911571

Modern advances in Artificial Intelligence (AI) and Machine Learning (ML) have transformed many businesses and elements of everyday life. Machine learning and deep learning support disease diagnosis, drug development, and patient risk assessment. This study examines how healthcare organizations evaluate enormous data sets using machine learning. This paper examines pros and downsides of current methods and research obstacles. Our goal is to educate healthcare professionals and government organizations on machine learning-based big data analytics in intelligent healthcare. AIML-powered chatbots enable governments educate and serve residents. They assist people get permits, answer questions, and use government services. Assistants help students make appointments, answer inquiries, and offer course material. Lead generation, product recommendations, and marketing efforts using AIML chatbots may boost revenue. AIML helps companies make data-driven decisions, find patterns, and recognize trends using data analysis and predictive analytics. Machine Learning studies how computers learn and improve without programming. Machine learning (ML) is a very captivating technology that has garnered significant interest over the course of technological advancements. As indicated by its nomenclature, this attribute endows the computer with a capacity that enhances its resemblance to human behaviour: the ability to acquire knowledge. © 2025 the Author(s).

关键词： Adversarial machine learning

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Robotic Grasp Detection for Medical Test Tubes Based on Convolutional Neural Network 2

Robotic Grasp Detection for Medical Test Tubes Based on Conv...

引用

2nd international conference on Automation, robotics and Computer engineering, ICARCE 2023

作者： Yin, Songtao Li, Maojun Jiang, Yiming Chen, Bo Zhang, Hui Zhao, Jiahao College of Electrical and Information Engineering Changsha University of Science and Technology Changsha China College of Electrical and Information Engineering Hunan University Changsha China School of Robotics Hunan University Changsha China

ISBN: (纸本)9798350308341

Visual-based robot grasping detection is a significant challenge in the field of robotics. With the widespread application of convolutional neural networks, significant progress has been made in this field in recent years. However, most of these methods only perform well on general objects, while their effectiveness is significantly reduced for small, smooth, and transparent medical test tube containers in medical scenarios. We propose a medical test tube dataset that specifically focuses on medical scenarios to address this issue. The dataset consists of 9 different types of medical test tubes, and over 200 sets of images were captured using a depth camera from various positions of the test tubes. Each set of images contains RGB information as well as depth information. Manual annotation was performed to label the grasping of the medical test tubes in the later stage. Furthermore, we introduce an end-to-end parallel feature fusion network that takes either RGB or depth maps as inputs and generates pixel-level grasp quality. Through experiments, our method achieves accuracies of 97.22%, 88.89%, and 83.33% on RGB images, depth images, and RGB-D images, respectively. These results validate the efficacy of our proposed approach for handling medical test tube containers. © 2023 IEEE.

关键词： Convolutional neural networks

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Automatic Detection of Diabetic Retinopathy Using CNN and SVM 2

Automatic Detection of Diabetic Retinopathy Using CNN and SV...

引用

2nd IEEE international conference on advances in Information technology, ICAIT 2024

作者： Anser Pasha, C.A. Bhargav, K.S. Akki, Ratan Sanath, R. Vismitha, V. Computer Science and Engineering Department Adichunchanagiri Institute of Technology Chikkamagluru India

ISBN: (纸本)9798350383867

Diabetic retinopathy is an eye disease caused by high sugar levels in blood, leaving the retina damaged. Retina is the part of the eye that detects the light and passes electrical signals to the brain. The optic nerve which connects retina and the brain helps the brain form the image of the objects that we see. Out of 5 diabetic patients, one suffers from diabetic retinopathy. Depending on the level of damage caused to retina, the diagnosed person can go through mild vision loss to total vision lost. Adopting automatic detection of diabetic retinopathy helps early diagnosis and reduce burden on the ophthalmologists enabling them to concentrate on higher priority cases. This paper discusses how CNN and SVM can be used to detect diabetic retinopathy with image processing concepts. ©2024 IEEE.

关键词： Ophthalmology

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Modeling of Soft Fingertip for Precise Sliding Prediction 8

Modeling of Soft Fingertip for Precise Sliding Prediction

引用

8th IEEE international conference on Advanced robotics and Mechatronics, ICARM 2023

作者： Yu, Jieji Ma, Xiaolong Zhou, Xuanyi Bao, Guanjun College of Mechanical Engineering Zhejiang University of Technology Hangzhou310023 China Ministry of Education and Zhejiang Province Zhejiang University of Technology Key Laboratory of Special Purpose Equipment and Advanced Processing Technology Hangzhou310023 China College of Mechanical and Electrical Engineering China Jiliang University Hangzhou310018 China

ISBN: (纸本)9798350300178

The dynamic slid process of soft fingertips on its object acts an important role in robotic grasping and in-hand manipulation. In order to study the deformation of the fingertip in this process, we regarded the soft fingertip as composed of a finite number of compressible and flexible cantilevers, and simulated the two-dimensional model of the soft fingertip, by focusing on the local displacement phenomenon and analyzing the sliding time sequence of the contacting point on the surface. We set up a finite element model for the sliding soft fingertip, and experimentally verified the local displacement change of the contact surface node when sliding occurs. Furthermore, a slip prediction method based on the position change pattern of the last sliding point under different initial normal grasping forces is proposed. © 2023 IEEE.

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Towards a Greener Tomorrow: IoT-Enabled Smart Environment Monitoring Systems

Towards a Greener Tomorrow: IoT-Enabled Smart Environment Mo...

引用

2023 international conference on advances in Computation, Communication and Information technology, ICAICCIT 2023

作者： Arya, Leena Sharma, Yogesh Kumar Kumar, Ramakrishna Koneru Lakshmaiah Education Foundation Department of Computer Science and Engineering Guntur AP Vaddeswaram India National University of Science and Technology College of Engineering Deputy Head-Department of Ece Muscat Oman

ISBN: (纸本)9798350344387

Integrating IoT technology into environmental monitoring systems offers solutions to contemporary sustainability challenges. This study explores IoT's potential to enhance environmental sustainability, focusing on improved air and water quality monitoring, resource-efficient precision agriculture, and waste management. It also addresses challenges such as cybersecurity risks and scalability. Ultimately, it underscores the pivotal role of IoT in advancing environmental sustainability, emphasizing the imperative of informed decision-making, use cases, and proactive measures to pave the way for a greener and healthier tomorrow. © 2023 IEEE.

关键词： Environmental Monitoring Internet of Things Smart Environment Sustainability

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Review on Coral Reef Regeneration Methods through Renewable Powered Electrotherapy 4

Review on Coral Reef Regeneration Methods through Renewable ...

引用

4th international conference on Clean and Green Energy engineering (CGEE)

作者： Elatfy, Ehsan Said, Lobna A. Fahim, Irene S. Radwan, Ahmed G. Nile Univ SESC Res Ctr Giza Egypt Nile Univ Nanoelect Integrated Syst Ctr NISC Giza Egypt Nile Univ SESC Res Ctr Ind Engn Program Giza Egypt Nile Univ Sch Engn & Appl Sci Giza Egypt Cairo Univ Engn Math & Phys Dept Cairo Egypt

ISBN: (纸本)9798350339796

The restoration of coral reef population in coastal regions is currently a growing concern. Many attempts have been made to apply new approaches to limit the deterioration of coral reefs, and to accelerate the growth of new reefs to protect coastal areas and ecosystems using available renewable energy sources. This paper highlights the new approaches and their various advantages and limitations in tidal and wave energy. The paper also suggests improvements to some of those systems using the recent developments in soft robotics, especially the use of biomimetic fish as a feasible support platform for the monitoring and maintenance of the power generation and potential restoration systems.

关键词： coral reefs wave harvesting soft robotics restoration renewable energy

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AI-Enabled Muscle Oxygen Sensors for Personalized Exercise Intensity Monitoring and Recovery Analysis 5

AI-Enabled Muscle Oxygen Sensors for Personalized Exercise I...

引用

5th IEEE international conference on advances in Electrical, Computing, Communication and Sustainable Technologies, ICAECT 2025

作者： Balachander, K. Balasubadra, K. Tidke, Bharat Sree Southry, S. Meenakshi, B. Murugan, S. R.M.K. College of Engineering and Technology Department of Artificial Intelligence and Data Science Puduvoyal Tamil Nadu Chennai India R.M.D. Engineering College Department of Information Technology Kavaraipettai Tamil Nadu Chennai India University Nagpur Campus Pune India Sona College of Technology Department of Electronics and Communication Engineering Tamil Nadu Salem India Sri Sairam Engineering College Department of Electrical and Electronics Engineering Tamil Nadu Chennai India Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Department of Biomedical Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350356236

Through the integration of artificial intelligence (AI) with muscle oxygen sensors, this work presents a unique way to exercise intensity monitoring and recovery analysis. Subjective assessments or heavy equipment are the backbone of the traditional approaches to evaluating exercise intensity and recovery. Using the latest developments in AI and wearable sensor technology, our system offers real-time personalized feedback to athletes and fitness enthusiasts. Our Muscle oxygen sensors were vigorously tested to ensure their precision and performance. Wearing the sensors, participants varied their workout regimen while the sensors sent data on the participants' muscle oxygen levels to an AI program. According to the results, the algorithm could correctly determine workout intensity levels and establish individual recuperation timeframes. Moreover, the AI system learns the user's physiological traits and can personalize recommendations and training programs for everyone. Our approach may help improve athletic performance, avoid overtraining injuries, and maximize fitness results by giving practical advice on recovering from exercises at the right intensity. © 2025 IEEE.

关键词： Sensory perception

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Deploying While Exploring: A Greedy-based Communication Beacons Deployment in Multi-Vehicle Exploration 4

Deploying While Exploring: A Greedy-based Communication Beac...

引用

4th international conference on Artificial Intelligence, robotics, and Communication, ICAIRC 2024

作者： Jin, Zhe Jia, Yifei Huang, Rui Zhang, Chengyang Jiang, Chaoyang Beijing Institute of Technology School of Mechanical Engineering Beijing China North Artificial Intelligence & Innovation Research Institute Collective Intelligence & Collaboration Laboratory China Beijing China Beijing Institute of Technology Yangtze Delta Region Academy Jiaxing China

ISBN: (纸本)9798331531225

In multi-vehicle collaborative exploration of unknown environments, it is still a great challenge to maintain the communication between multiple vehicles. In this paper, we present a greedy-based communication beacon deployment method to address this challenge. The proposed method involves each vehicle performing LiDAR-inertial odometry, hierarchical grid-based exploration, and greedy-based beacon deployment. Each time a vehicle reaching the communication boundary, beacon candidate positions are selected. A candidate location that can cover the most uncommunicated area is selected as beacon placement points. Through simulation experiments, the effectiveness of the proposed method is demonstrated, showing that it can dynamically deploy beacons to maintain communication within the explored area while minimizing the number of beacons used. © 2024 IEEE.

关键词： Vehicle-to-grid

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Research on Collision Detection Method Based on Feature Extraction 6

Research on Collision Detection Method Based on Feature Extr...

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6th international conference on robotics, Intelligent Control and Artificial Intelligence, RICAI 2024

作者： Lv, Haodi Lan, Ting Shi, Jianye Lv, Ming Wang, Yue Faculty of Electrical Engineering and Computer Science Ningbo University Ningbo China Loctek Ergonomic Technology Corp Ningbo China

ISBN: (纸本)9798331541699

Research the collision detection problem during equipment operation. Collect data on collisions occurring at different positions during normal operation and operation of the equipment, process the signals using wavelet transform, extract feature indicators such as kurtosis for analysis, and finally use Support Vector Machine (SVM) classification method to distinguish collisions and their specific locations. The research results show that using the One-Versus-Rest (OVR) classification method with a lifting table as the experimental object, the accuracy of the data reaches 96.11%, the classification time is 0.021, and it has high detection and discrimination rates. Moreover, this method can effectively detect collisions during equipment operation based on the collected data and determine the specific location of the collision. © 2024 IEEE.

关键词： Wavelet transforms

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