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

共 46800 条记录，以下是121-130 订阅

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An Automatic Detection of Counterfeit or Damaged Indian Rupee Notes 15

An Automatic Detection of Counterfeit or Damaged Indian Rupe...

引用

15th international conference on advances in Computing, Control, and Telecommunication Technologies, ACT 2024

作者： Deepak, N.R. Pal, Simran R. Yasmeen, Nikhat Amin, Omar Ismail Sahu, Ankit Kumar Suhas, G.K. Department of Computer Science Engineering Atria Institute of Technology Karnataka Bengaluru India Department of Computer Science Engineering HKBK College of Engineering Karnataka Bengaluru India Department of Information Science Engineering Akshaya Institute of Technology Karnataka Tumkur India

ISBN: (纸本)9798331300579

Every year in India, the Reserve Bank of India (RBI) deals with the issue of counterfeit currency *** employees are highly educated to detect counterfeit notes, however the trouble comes when such notes are used blended into the market and distributed via common channels *** counterfeit notes from ATMs is also a *** also been observed in several *** the past, In the last few years, as a result of incredible technological. © Grenze Scientific Society, 2024.

关键词： Fake Currency RBI

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Augmented Differential Dynamic Programming for Humanoid Robot Flipping Motion Optimization 9

Augmented Differential Dynamic Programming for Humanoid Robo...

引用

9th international conference on robotics and Automation engineering, ICRAE 2024

作者： Jin, Mingyue Gao, Junyao Cao, Jingwei Jin, Xiaokun Xie, Leilei Xin, Xilong Beijing Institute of Technology School of Mechanical Engineering Beijing China Beijing Institute of Technology School of Medical Technology Beijing China

ISBN: (纸本)9798331518301

Differential Dynamic Programming (DDP) is an efficient tool for non-linear optimal problems. And DDP shows a characteristic of fast convergence. However, the traditional DDP cannot solve the nonlinear constraints. Therefore, an augmented differential dynamic programming method is proposed in this paper for trajectory optimization of humanoid robot motion planning. The flipping motion is adopted in our work. The continuous dynamic model and collision dynamic model are constructed, in which the reset map of the collision dynamics model calculates the instantaneous velocity and acceleration change before and after the collision. Moreover, the Augmented Lagrangian (AL) method is adopted in DDP to deal with equality constraints and inequality constraints. After n times of augmented DDP iterations, the optimal flipping motion trajectory is obtained. The simulation experiments on the BHR-FCR humanoid robot show that the proposed approach has the ability to solve nonlinear constraint optimal problems. © 2024 IEEE.

关键词： Anthropomorphic robots

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Greensense: IoT-Enabled Smart Monitoring And Early Detection System For Optimal Plant Health In Greenhouse

Greensense: IoT-Enabled Smart Monitoring And Early Detection...

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2024 international conference on advances in Data engineering and Intelligent Computing Systems, ADICS 2024

作者： Venkatesh, R. Aadhira, K.R. Kathiravan, M. Hindustan Institute Of Technology And Science Department Of Computer Science & Engineering Chennai India

ISBN: (纸本)9798350364828

The emergence of Agriculture 4.0 signifies a transformative shift in traditional farming practices, integrating cutting-edge technologies like IoT, machine learning, and robotics to support productivity and sustainability. This era leverages real-time data and automation for precision farming, predictive analytics, and resource optimization, crucial for addressing global food security challenges while minimizing environmental impact. GreenSense represents progress within Agriculture 4.0. It seeks to revolutionize greenhouse management by integrating IoT and advanced machine learning algorithms. Through sensors, actuators, and a Raspberry Pi 4 board, this system offers a comprehensive solution for monitoring and optimizing plant health in controlled environments. The motivation behind this system stems from the imperative to enhance agricultural practices sustainably in the face of population growth. By enabling real-time monitoring and swift anomaly detection through application, this paper empowers proactive intervention to mitigate risks and optimize growing conditions. Integration of the YOLOv5 algorithm with 97% accuracy enhances precision in leaf disease and pest detection using OpenCV, reducing crop losses effectively. Beyond greenhouse management, this paper contributes to advancing sustainable agriculture. Its scalable and adaptable nature promotes resource-efficient practices and environmental care. Finally, a user-friendly interface is tailored to facilitate efficient data collection from sensors, enabling comprehensive monitoring of crop conditions, including pest and disease detection. © 2024 IEEE.

关键词： Learning algorithms

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Design and Implementation of Hand Exoskeleton for Rheumatoid Arthritis Rehabilitation

Design and Implementation of Hand Exoskeleton for Rheumatoid...

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2025 IEEE international Students' conference on Electrical, Electronics and Computer science, SCEECS 2025

作者： Balaji, Sudharshan Jaba Deva Krupa, A. Bharanidivya, Madhavan Dhanalakshmi, Samiappan Srm Institute of Science and Technology College of Engineering and Technology Department of Electronics and Communication Engineering Chennai603203 India

ISBN: (纸本)9798331529833

Inflammation of the joints is a hallmark of rheumatoid arthritis (RA), a long-term inflammatory disease that can cause significant discomfort, limited range of motion, and impaired hand function. Developing a tailored hand exoskeleton to help RA patients carry out routine activities and regain some dexterity in their hands is the primary goal of this study. This exoskeleton is designed specifically for RA sufferers. It uses precise actuation technology and soft, adaptable materials to help in gripping and finger extension without making the patient uncomfortable or requiring them to move against their will. With its built-in sensors, the exoskeleton keeps tabs on the user's every motion, analyzing their joint locations and patterns to provide real-time feedback and tailor adjustments to their specific mobility and pain. RA sufferers will be able to modify the support levels of the exoskeleton based on the type of activity they are performing and the amount of pain they are experiencing. Control will be achieved through an interface that is easy to use. This project aims to produce an assistive device that improves the quality of life for individuals with rheumatoid arthritis (RA) by boosting freedom in daily activities while minimizing joint stress. This will be accomplished by merging several biomedical principles with modern robotics. © 2025 IEEE.

关键词： Exoskeleton (robotics)

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Shape Estimation of Travel Path Using Reservoir Computing for Water-Driven Soft Robot 11

Shape Estimation of Travel Path Using Reservoir Computing fo...

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11th international conference on Mechatronics and robotics engineering, ICMRE 2025

作者： Mieno, Junya Sumioka, Hidenobu Takuma, Takashi Osaka Institute of Technology Department of Electrical and Electric Systems Engineering Osaka Japan Atr Kyoto Japan

ISBN: (纸本)9798331509293

A soft robot has a significant advantage regarding its locomotion that it can change its shape passively based on its path shape variations. In this study, we adopt reservoir computing (RC), a kind of recurrent neural network, to classify five types of path shapes based on the inner pressure in the flexible chambers of the developed robot. By using small sets of the time-varying pressure waveform, we found that RC with an appropriate number of neurons could accurately classify the path shapes. © 2025 IEEE.

关键词： Industrial robots

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Predictive Analysis of Diabetes Data in Healthcare System Using Machine Learning Algorithms 4

Predictive Analysis of Diabetes Data in Healthcare System Us...

引用

4th international conference on robotics, Electrical and Signal Processing Techniques, ICREST 2025

作者： Al Arafat, Kazi Abdullah Al Amin Rahman, Md Siddique, Sumaya Roni, Mahmudur Rahman Parvez, Imtiaz Atish Dipankar University of Science and Technology Department of Computer Science and Engineering Dhaka Bangladesh American International University Department of Computer Science and Engineering Dhaka Bangladesh Utah Valley University Department of Computer Science 800 W University Pkwy OremUT84058 United States

ISBN: (纸本)9798331530938

Diabetes, influenced by factors like high blood pressure, aging, obesity, and poor lifestyle choices, has become a significant health issue, increasing the risk of heart disease, kidney disease, stroke, and other serious conditions. Traditional diagnostic methods in hospitals can sometimes be misleading, underscoring the need for big data analysis in healthcare. This approach can uncover hidden patterns in diabetes-related data, enabling more accurate predictions of outcomes. This paper aims to classify large diabetes datasets to predict the disease's behavior using various attributes. A machine learning model with sixteen classifiers, fine-tuned through k-fold cross-validation, was developed to ensure optimal results, with accuracy measured by F1 score, precision, and recall. © 2025 IEEE.

关键词： Adversarial machine learning

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Large Language Models in AWS 1

Large Language Models in AWS

引用

1st international conference on robotics, engineering, science, and technology, RESTCON 2024

作者： Kodali, Ravi Kishore Prasad Upreti, Yatendra Boppana, Lakshmi National Institute of Technology Warangal Department of Electronics and Communication Engineering Warangal India

ISBN: (纸本)9798350348842

Large Language Models (LLMs) have become a transformative milestone in natural language processing. The deployment of LLMs on cloud platforms like Amazon Web Services (AWS) plays a pivotal role in making their capabilities accessible to a wider audience, contributing to the democratization of advanced language processing technology. This paper reviews the evolution of cloud application architectures, focusing on transferring cloud applications across various infrastructures, offering insight for cloud engineers and architects. Throughout this paper, we dive into the intricacies of deploying Llama-2 on various AWS instance types, each tailored to specific use cases and computational requirements. The analysis highlighted trade-offs between factors such as computational speed, cost efficiency, and resource utilization, all of which play a crucial role when working with the LLM model. Additionally, we compared instance performance, emphasizing the role of max-batch-prefill tokens in enhancing response generation efficiency. The results provide a clear understanding of the impact of instance-Type selection on the model's performance, allowing informed decisions to be made based on specific language processing requirements. © 2024 IEEE.

关键词： Economic and social effects

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A fixed-time stable underwater manipulator time-varying delay teleoperation system with input saturation 7

A fixed-time stable underwater manipulator time-varying dela...

引用

7th international conference on robotics, Control and Automation engineering, RCAE 2024

作者： Gao, Yixuan Ji, Yude Hebei University of Science and Technology School of Sciences Shijiazhuang China

ISBN: (纸本)9798350355642

In this paper, we consider the problem of bilateral teleoperation of underwater manipulators with time-varying delay, input saturation, and system stability that can be achieved at a fixed time. A non-general prescribed performance function is added to the terminal sliding surface and a virtual system is introduced to overcome the difficulties caused by actuator saturation. Based on the terminal sliding surface, a control scheme is designed to achieve the prescribed performance of position synchronization and virtual error. The stability of the system is proved using the barrier Lyapunov function theory, and a fixed bound on the global settling time is further calculated. Finally, the feasibility and effectiveness of the scheme are verified by simulation experiments. © 2024 IEEE.

关键词： Time varying control systems

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Efficient Kinematic Calibration for Industrial Manipulators based on a Simplified POE model 7

Efficient Kinematic Calibration for Industrial Manipulators ...

引用

7th international conference on robotics, Control and Automation engineering, RCAE 2024

作者： Wang, Jin Fang, Ziyang Yu, Chenchen Zhang, Haiyun Zheng, Zhi Lu, Guodong Zhejiang University School of Mechanical Engineering Hangzhou China Zhejiang University Polytechnic Institute Hangzhou China Ningbo University of Technology School of Robotics Ningbo China

ISBN: (纸本)9798350355642

The Product-of-Exponential (POE) model simplifies kinematic modeling by establishing direct relationships between kinematic and end-effector errors using base coordinate and tool coordinates. However, It contains numerous parameters and high latitude, which may lead to reduced efficiency and precision in the case of limited test data. This paper introduces the Simplified Effective Kinematic Calibration (SEC) technique, combining the Simplified Product-of-Exponential (SPOE) model, Pre-processing Sequential Quadratic Programming (PSQP), and Gaussian Process Regression (GPR) to enhance calibration accuracy and efficiency. The SEC technique reduces parameter identification dimension, identifies coordinate transformation, compensates for geometric errors, and uses GPR for non-geometric error compensation. Experiments show that SEC demonstrates better positioning accuracy and efficiency than traditional methods. © 2024 IEEE.

关键词： Error compensation

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Unsupervised Monocular Depth Estimation Based on Local Planar Guidance Layer

Unsupervised Monocular Depth Estimation Based on Local Plana...

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international conference on Computer Vision, robotics, and Automation engineering, CRAE 2024

作者： Q., Zhang Q., Shi T., Cheng Hefei University of Technology Key Laboratory for Automated Vehicle Safety Technology of Anhui Province Engineering Research Center for Intelligent Transportation and Cooperative Vehicle-Infrastructure of Anhui Province School of Automotive and Transportation Engineering Hefei230009 China Chery Automobile Co. Ltd. Wuhu China

ISBN: (纸本)9781510682283

As computer vision technology advances, depth estimation has garnered significant interest for addressing depth perception challenges in the field. However, traditional unsupervised monocular infrared image depth estimation methods have difficulty dealing with issues such as edge blurriness and occlusions, resulting in poor depth estimation performance. Therefore, this paper proposes an enhanced DispNet network with local planar guidance layer for unsupervised monocular infrared image depth estimation. Firstly, it addresses the problems of edge blurriness and occluded objects in infrared images through the utilization of multiple small-resolution grayscale blocks and multi-scale feature fusion. Secondly, a plane constraint is introduced on the depth map in the local planar guidance layer to reduce noise and discontinuities in the depth map. On the infrared image dataset Iray, the Abs Rel and RMS log were 0.262 and 0.332, respectively, with an accuracy rate of 94.5% when the threshold metric was less than 1.253. The experimental results reveal that the algorithm achieves the expected effect on infrared images, and can provide more reliable visual perception performance when driving at night. © 2024 SPIE.

关键词： Infrared imaging

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