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

共 47675 条记录，以下是541-550 订阅

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Blind Lane Detection and Following for Assistive Navigation of Vision Impaired People 8

Blind Lane Detection and Following for Assistive Navigation ...

引用

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

作者： Han, Zhicheng Gu, Jason Feng, Ying Institute of Advanced Technology University of Science and Technology of China Hefei230031 China Dalhousie University Department of Electrical and Computer Engineering HalifaxNS Canada College of Automation Science and Engineering South China University of Technology Guangzhou510641 China

ISBN: (纸本)9798350300178

The task of safely navigating outdoor environ-ments presents significant difficulties for people with visual impairments. This paper aims to address this issue by proposing a wearable assistance system for visually impaired individuals in blind lane detection and following scenarios. The system consists of two stages: the first stage employs a fully convolutional network to detect blind lanes and an object detection network to identify obstacles. The second stage utilizes an improved artificial potential field method to achieve real-time path following based on the detection results. Our experiments involving subjects in dynamic outdoor environments demonstrate the robustness of our proposed method in navigating and avoiding obstacles under challenging outdoor conditions. © 2023 IEEE.

关键词： Object detection

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Designing Optimal Parameters for Single-Axis Solar-Tracker through Analysis of Sun-Path and Tracking Vector Dynamics 6

Designing Optimal Parameters for Single-Axis Solar-Tracker t...

引用

6th international conference on Electrical engineering and Information and Communication technology, ICEEICT 2024

作者： Akhtaruzzaman, M. Islam, Md Shofiqul Shahryer, Fahim Arif, Muammer Din Mollik, Md. Sazib Rahman, Muhammad Towfiqur Rahman, Md. Mahbubur Hasan, Mohammad Kamrul Ahmed, Shugata Ashrafuzzaman, Md. Department of Computer Science and Engineering Dhaka1216 Bangladesh Department of Mechanical Engineering Dhaka1216 Bangladesh Department of Electrical and Electronic Engineering Dhaka Bangladesh Department of Computer Science and Engineering Dhaka Bangladesh Faculty of Information Science and Technology Bangi Malaysia Department of Robotics and Mechatronics Engineering Bangladesh Sdn. Bhd. Cyberjaya Malaysia

ISBN: (纸本)9798350385779

The persistent challenges faced by sun-tracking systems include inefficient power production, wastage of energy, ineffective control, and high costs. Most of the existing systems are either static or dual-axis tracking which lead to inefficient output or increasing energy wastage and cost overheads. Though, single-axis tracking system has some benefits over the static or dual-axis tracking, most of the systems do not analyze the selection of optimal sun-path which again leads to inefficient and inadequate absorption of sunlight. Addressing the issues, this article presents a design of optimal parameters for single-axis solar-tracking by analyzing the sun-path and tracking vector dynamics. The study mainly focuses on analyzing solar-tracking dynamics, variations in sunray angles, Azimuth and Elevation dynamics throughout the day for the twelve months, Sun-vector calculation for local coordinates, joint rotational-axis, and joint motion control using a Proportional-Derivative controller. Additionally, the article outlines a conceptual architecture for automated control, monitoring, and power distribution for the potential development of a sustainable smart city. The proposed strategy addresses the issues of the optimal design of a single-axis solar-tracker, thus ensuring the reduction of cost overhead and energy wastage. © 2024 IEEE.

关键词： Dynamics

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Tuning of a Robotic Arm using PID Controller for robotics and Automation Industry 6

Tuning of a Robotic Arm using PID Controller for Robotics an...

引用

6th international conference on Energy, Power and Environment, ICEPE 2024

作者： Kulkarni, Palvi Kulkarni, Ovi Sayyad, Javed K. Symbiosis Institute of Technology Maharashtra Pune India

ISBN: (纸本)9798350379297

This paper discusses integrating robotics and automation systems to improve industrial automation's efficiency, precision, and reliability, focusing on the versatile robotic arm. The study explores Auto PID tuning for controlling robotic arms through MATLAB Simulink for dynamic performance optimization. The paper systematically examines PID implementation and tuning PID techniques and compares them to other controllers. In this way, it provides invaluable insights into automation control technologies. The research focuses on designing and auto-tuning a PID controller in real-time for efficient robotic arm *** PID controller is the best option for robotic arm operation as it allows dynamic parameter modification and precise trajectory tracking. Finally, the study stresses the PID controller's efficiency and effect in improving industrial robotic arms' performance. It thus enables smooth operation and increases productivity in the manufacturing environment. © 2024 IEEE.

关键词： Robotic arms

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Efficient Novel Method for EEG Signal Classification in Epileptic Seizure Identification using Metaheuristic Deep Learning

Efficient Novel Method for EEG Signal Classification in Epil...

引用

2024 IEEE international conference on Recent advances in science and engineering technology, ICRASET 2024

作者： Pokkuluri, Kiran Sree Nigam, Nishesh Fuskele, Avita Raja, C. Shukla, Prashant Kumar Chhaya Shri Vishnu Engineering College for Women Department of Computer Science and Engineering Bhimavaram India Ies Institute of Technology and Management Ies University Department of Computer Science and Engineering MP Bhopal462044 India Jabalpur Engineering College Information Technology Department Jabalpur India Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Tamil Nadu Chennai India Koneru Lakshmaiah Education Foundation Department of Computer Science and Engineering Vaddeswaram Guntur India Mangalayatan University Jabalpur India

ISBN: (纸本)9798350388602

Using a metaheuristic deep learning strategy, the research focuses on the challenge of epileptic seizure detection. A diagnostic tool known as an electroencephalogram (EEG) may detect improperly functioning brain cells, the underlying cause of seizures. To enhance the precision of seizure detection, the offered approach merges deep learning with a metaheuristic optimization technique. This method involves preprocessing raw EEG data in order to extract fundamental characteristics. A classifier that is part of a deep learning system is subsequently fed these characteristics in stages. When it comes to finding a decent solution with high accuracy dimensions, the metaheuristic component finds the optimal values for the deep learning model. Due to the sluggish convergence and trapping of local minima in standard clustering methods, this approach seeks to improve detection performance. Using industry standard EEG datasets, we evaluate our hybrid technique's performance to that of other relevant models. These findings demonstrate that the system is a dependable tool for real-time seizure detection, with sensitivity, specificity, and accuracy all surpassing the current standards. This method stands head and shoulders above its predecessors, proving its viability for clinical usage in epilepsy monitoring and diagnosis. © 2024 IEEE.

关键词： Electroencephalography

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Development of Deep Learning-based for Hot-rolled Seamless Steel Pipes' Outer Surface Defect Recognition System

Development of Deep Learning-based for Hot-rolled Seamless S...

引用

2024 lEEE international conference on Advanced Information, Mechanical engineering, robotics and Automation, AIMERA 2024

作者： Wang, Xueyuan Chen, Jiaqi Liu, Guodong Hu, Lijie Wang, Xiaochen Yang, Quan University of Science and Technology Beijing School of Mechanical Engineering Beijing China University of Science and Technology Beijing Institute of Engineering Technology Beijing China Chengde Jianlong Special Steel Co. Ltd Technology R&D Department Chengde China

ISBN: (纸本)9798350343335

Detecting surface defects is crucial during the production process of hot-rolled seamless steel pipes. In order to make up for the shortcomings of traditional inspection methods, this study developed a set of surface defect detection systems of hot-rolled seamless steel pipe by 3D point cloud and deep learning. A 3D point cloud-based defect detection equipment for seamless steel pipe outer surface was developed to achieve full coverage of seamless steel pipe outer surface detection. The defect detection model of seamless steel pipe surface was designed based on the YOLOF algorithm of correcting attention mechanism, and the corresponding software system was developed for online identification. To confirm the efficacy of the proposed approach, the defect pictures collected by a steel pipe factory were used as an implementation case. The experimental results confirm that all types of defects are effectively covered with a detection rate exceeding 99%, while maintaining a false detection rate of under 0.08%. The industrial application shows that compared with the current advanced detection method, the false positive rate of the outer surface is reduced by 9.5% on average. The proposed method has low installation and maintenance costs, which can lay a foundation for further application of seamless steel pipe quality determination, analysis, and control. © 2024 IEEE.

关键词： Point defects

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Conservative Power Theory Approach for Feature Extraction in Non-Intrusive Load Monitoring 4

Conservative Power Theory Approach for Feature Extraction in...

引用

4th IEEE international conference on Recent advances in Systems science and engineering, RASSE 2024

作者： Munthe, Romario Oktavelen Ginting Lian, Kuo-Lung Suwarno Hariyanto, Nanang Primaghani, Kaisar Fabhila The Department of Electrical Engineering National Taiwan University of Science and Technology Taipei Taiwan Department of Electrical Engineering Bandung Institute of Technology Bandung Indonesia

ISBN: (纸本)9798331528263

Non intrusive load monitoring offers a cost-effective alternative traditional energy monitoring by disaggregating a household’s total energy consumption into individual appliance loads from a single measurement point. This technology enhances energy conservation, demand-side management, and smart grid development However, there are many electric appliances exhibit similar operational characteristics because they share similar front end or have similar core technology. This is one of the most challenging and important task in NILM because there is an increasing trend in electric appliances to use active front ends for better energy efficiency. In this paper, we demonstrate that feature extraction based on conservative power theory (CPT) performs better, compared to Fryze’s method in discerning loads with similar core technology or sharing the same front ends. Incorporating a feature extraction layer based on CPT into a deep learning neutral network can achieve an F1 score of 0.946, compared to those based on Fryze’s method and the Vanilla case (i.e. no feature extraction layer), which correspond to 0.875 and 0.685, respectively to identify the turn-on and turn-off status of a total of 1023 load combinations. © 2024 IEEE.

关键词： Energy utilization

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Reconstructing Global Multi-Person 3D Motions from a Single Moving Camera

Reconstructing Global Multi-Person 3D Motions from a Single ...

引用

2024 IEEE international conference on robotics and Biomimetics, ROBIO 2024

作者： Zhao, Boxin Zhang, Hanxiang Liu, Wei Gu, Jason Dalhousie University Department of Electrical and Computer Engineering HalifaxNS Canada South-ern University of Science and Technology Department of Mechanical and Energy Engineering 1088 Xueyuan Avenue Shenzhen518055 China

ISBN: (纸本)9781665481090

Currently, the reconstruction of global human trajectories from in-the-wild videos represents a highly promising research area, with applications derived from this technology becoming more practical and widespread. To address the challenges of depth ambiguity and occlusions in monocular videos, we propose an optimization-based framework combining SLAM techniques and human motion priors to recover global multi-person motions from a single moving camera. Our approach employs SLAM techniques to estimate camera parameters and utilizes an advanced tracking algorithm to alleviate occlusions. We also incorporate a learned motion smoothness prior into the optimization framework and optimize SMPL models and camera parameters to fit detected 2D poses. On the 3DPW dataset, our method can achieve superior performance over previous work. © 2024 IEEE.

关键词： 3D reconstruction

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Research on Ascent Phase Guidance technology Based on Uncertainty Parameter Online Identification

Research on Ascent Phase Guidance Technology Based on Uncert...

引用

2024 IEEE international conference on Control science and Systems engineering, ICCSSE 2024

作者： Yichong, Shao Jiayuan, Ding Chunzhen, Sun Mengmeng, Cui College of Automation Engineering Nanjing University of Aeronautics and Astronautics Nanjing China China Academy of Launch Vehicle Technology Beijing China

ISBN: (纸本)9798331517199

In response to the challenges of numerous constraints in the ascent phase of composite-powered carriers, narrow flight corridors, and poor adaptability of guidance to deviations in aerodynamic coefficients, atmospheric density, and thrust, this paper proposes an ascent guidance method based on online identification of uncertain parameters. An online identification model based on acceleration information is established to identify the magnitude of parameter deviations. Trajectory profiles matching the magnitude of parameter deviations are selected online from a trajectory database to ensure that the guided vehicle reaches the starting window of the next mission within the constraints under deviation conditions. Simulation results demonstrate that this method enables rapid online selection of a trajectory adapted to the current composite uncertainties, thereby enhancing the robustness of ascent phase guidance schemes for composite-powered carriers. © 2024 IEEE.

关键词： Atmospheric density

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Research on Welding trajectory planning of MOTOMAN-MA1440 robot based on MATLAB robotics Toolbox 3

Research on Welding trajectory planning of MOTOMAN-MA1440 ro...

引用

3rd international conference on Control and Intelligent robotics, ICCIR 2023

作者： Pan, Yunping Lu, Yongqi Liu, Chao School of Mechanical and Electrical Engineering Wuhan University of Technology WuHan430000 China

ISBN: (纸本)9781510671867

In order to analyze the welding trajectory of the rear axle weld on a drive axle, the kinematics equation of the robot was established using the D-H parameter method. MATLAB robotics Toolbox was utilized to verify the forward and inverse kinematics through simulation and to plan the trajectory, continuous and stable terminal pose, change curves of Angle, angular velocity and angular acceleration were obtained. By incorporating specific weld points on the workpiece, the fitting toolbox in MATLAB was employed for curve fitting. The results demonstrate a strong alignment between the trajectory curve fitted by the actual welding points and the simulated trajectory curve. It provides theoretical support for the further research of MOTOMAN-MA1440 robot. © 2023 SPIE.

关键词： MATLAB

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Enhancing Information Extraction from Long Document: Utilizing LLM’s Prompt engineering for Long Document Set Generation 5

Enhancing Information Extraction from Long Document: Utilizi...

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5th international conference on Control, robotics, and Intelligent System, CCRIS 2024

作者： Xiao, Liyong Cao, Xiaoli Tang, Can Lai, Xuan Zhu, Xiuling Han, Zhiqiang The Artificial Intelligence College of Chongqing Technology Business University Chongqing China Chongqing Key Laboratory of IntelliSense and Blockchain Technology Chongqing China

ISBN: (数字)9781510685871

ISBN: (纸本)9781510685864

Large Language Models (LLMs) face challenges such as outdated knowledge, generation illusions, and opaque reasoning processes. To address these challenges, Retrieval-Augmented Generation (RAG) has emerged as a solution by integrating external knowledge bases. However, traditional RAG encounters bottlenecks when dealing with long documents, such as information loss, incoherence, and low query precision at the granularity level. To tackle these issues, a novel method based on prompt engineering for efficient extraction of information from long documents is proposed. Firstly, a prompt engineering-based document segmentation algorithm is introduced to enhance the model’s capability to handle long document inputs. Then, utilizing prompt engineering, long documents are transformed into structured long document datasets with hierarchical summaries, including titles, headings, abstracts, and keywords, highlighting key information points to enhance document understanding and retrieval matching efficiency. Experimental results demonstrate that this method significantly improves the quality and precision of information extraction from long documents, outperforming traditional retrieval-augmented generation paradigms, thus paving the way for the development of interactive question-answering systems tailored for multi-document, multi-knowledge point scenarios. This method efficiently locates relevant content in long document sets based on query semantics, providing precise responses. © 2024 SPIE.

关键词： Semantics

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