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

共 47670 条记录，以下是281-290 订阅

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Fuzzy-PID vs. PID Controllers: A Comparative Study on DC Motor Speed Control 1

Fuzzy-PID vs. PID Controllers: A Comparative Study on DC Mot...

引用

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

作者： Prasoetphon, Tanakorn Selamassakul, Kasit Sittiwanchai, Teppakorn Jitviriya, Wisanu King Mongkut's University of Technology North Bangkok Department of Production and Robotics Engineering Bangkok Thailand

ISBN: (纸本)9798350348842

In this study, an educational experimental kit is introduced to provide a comprehensive comparison of PID and Fuzzy-PID controllers in the context of DC motor speed control. The experimental setup incorporates an incremental encoder to accurately measure motor speed, while a user-friendly graphical user interface (GUI) enables seamless interaction with the system. The performance of both controllers is thoroughly evaluated based on four critical parameters or can be called that time-domain specifications: rise time, overshoot, steady-state error, and settling time which these can be displayed on graphical user interface to analyze the characteristic of speed of DC motor. Additionally, the theoretical underpinnings of each controller type are discussed, illustrating the distinct advantages and drawbacks associated with each approach. The project aims to offer a hands-on learning experience, deepening students' understanding of these two prevalent control strategies and empowering them to make informed decisions when selecting the most suitable controller for various applications. © 2024 IEEE.

关键词： DC motors

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Revolutionizing Healthcare with Federated Learning: A Comprehensive Review

Revolutionizing Healthcare with Federated Learning: A Compre...

引用

2024 international conference on advances in Computing Research on science engineering and technology, ACROSET 2024

作者： Mishra, Snehlata Tondon, Ritu Rathore, Narendra Pal Singh Sage University Computer Science & Engineering Indore India Acropolis Institute of Technology and Reserach Computer Science & Engineering Indore India

ISBN: (纸本)9798350388800

Federated learning has become a game-changing paradigm in healthcare, offering secure and private federated model training across dispersed data sources. This thorough analysis examines the uses, developments, and challenges of federated learning in healthcare. Beginning with an elucidation of its fundamental principles, we examine its potential to revolutionize healthcare delivery by facilitating collaborative model training without data sharing. We survey diverse applications, including disease diagnosis, personalized treatment recommendations, drug discovery, and population health management, highlighting federated learning's impact on improving patient outcomes and healthcare efficiency. Technological advancements, such as differential privacy and secure aggregation, driving federated learning adoption, are explored. Despite its promise, federated learning faces challenges including data heterogeneity, model communication overhead, privacy concerns, and regulatory barriers. We discuss these challenges and propose solutions and future research directions. This review provides a comprehensive understanding of federated learning's role in healthcare, addressing opportunities, limitations, and future prospects. © 2024 IEEE.

关键词： Collaborative learning

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SAT Problem Solving based on Hybrid Grey Wolf Genetic Algorithm 7

SAT Problem Solving based on Hybrid Grey Wolf Genetic Algori...

引用

7th international conference on Intelligent robotics and Control engineering, IRCE 2024

作者： Li, Ya Sun, Yu Tong Lv, Hong Yang Chen, Lei Qu, Tian Wei Yun, Hai Hong Heilongjiang Institute of Technology College of Computer Science and Technology Harbin China Institute for Advanced Ceramics School of Materials Science and Engineering Harbin Institute of Technology Harbin China

ISBN: (纸本)9798350352399

A hybrid algorithm based on grey wolf optimization algorithm, genetic algorithm, and heuristic information is proposed for solving SAT problems. The algorithm is an incomplete algorithm. To solve the problem that the retention of dominant individuals in the standard genetic algorithm depends on selection probability, the grey wolf optimization algorithm is introduced into the crossover operator to increase the probability of inheriting dominant individuals to new generation. At the same time, there is also a significant randomness in mutation operation, which makes the entire algorithm prone to falling into local optima and the convergence speed is too slow. Therefore, in mutation operator, select those variables whose values can satisfy more clauses, to jump out of local optima while accelerating the convergence speed of the algorithm. Through comparative experiments, it was found that the algorithm proposed in this paper can quickly solve satisfying problems, and the algorithm is efficient and stable. © 2024 IEEE.

关键词： Optimization algorithms

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Obstacles Avoidance Path Planning for Mobile Robot Based on Cellular Automata 6

Obstacles Avoidance Path Planning for Mobile Robot Based on ...

引用

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

作者： Li, Lili Li, Wenwei Huang, Jinglun School of Automation Science and Engineering South China University of Technology Guangzhou China Institute of Intelligent Manufacturing Shunde Polytechnic Foshan China Department of Technical Research South China Robotics Innovation Research Institute Foshan China Foshan Zhiyouren Technology Co. Ltd. Foshan China School of Electronics and Information Engineering Wuyi University Jiangmen China

ISBN: (纸本)9798331541699

In order to quickly plan the shortest path for mobile robot in two-dimensional space, a two-stage obstacles avoidance path planning algorithm based on cellular automata was presented in this paper. For the first stage, the distance between each free cell to the ending cell was gradually generated by the evolution of cellular automata, and the algorithm’s cellular space, cellular states, Moore type neighbors and evolutionary rules were described, respectively. For the second stage, by using the idea of the negative gradient, a method of generating the shortest path based on the cells’ state values was proposed. Accordingly, the corresponding flow chart and Matlab programme of the algorithm were designed. The effectiveness of the algorithm was verified by the simulation and the physical experiment. The results showed that the shortest path in complex environment can be efficiently planned by using our cellular automata algorithm. © 2024 IEEE.

关键词： Microrobots

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Back-stepping Prescribed-Time Sliding Mode Control of a Quadrotor UAV 12

Back-stepping Prescribed-Time Sliding Mode Control of a Quad...

引用

12th RSI international conference on robotics and Mechatronics, ICRoM 2024

作者： Badiei, Roozbeh Sajjadi, Mohammad Bagher Ayati, Moosa Davaie-Markazi, Amir Hossein School of Mechanical Engineering Iran University of Science and Technology Tehran Iran School of Mechanical Engineering College of Engineering University of Tehran Tehran Iran

ISBN: (纸本)9798331529734

This paper introduces a novel approach that integrates a Back-stepping Prescribed-Time Control (PTC) framework combined with Sliding Mode Control (SMC) to achieve trajectory tracking of a quadrotor in a user-defined preset time. The proposed control strategy not only achieves precise trajectory tracking but showcases resilience to variations in initial conditions and different preset times. The results obtained from simulations depicted the efficiency of the proposed control strategy in trajectory tracking of both rotational and transnational subsystem of the drone. Furthermore, the superior performance of the proposed control over a traditional PID control has been investigated, depicting notable overshoot reductions in control signals. © 2024 IEEE.

关键词： Sliding mode control

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Research on Path Planning System for Vision-Based Control of Micro-Robots

Research on Path Planning System for Vision-Based Control of...

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2024 international conference on Computing, robotics and System sciences, ICRSS 2024

作者： Xie, Kadan Zhu, Xingrong Zhou, Ying Wang, Dan Huang, Xiaoxiang College of Mechanical and Electrical Engineering Guangdong University of Science and Technology Guangdong Dongguan China Bangi Malaysia

ISBN: (纸本)9798331511296

This paper presents a path-planning system for micro-robots based on machine vision, designed to enable the efficient control of micro-robot swarms. Micro-robots have diverse applications in fields such as industry and education, including precision assembly, product inspection, teaching demonstrations, and scientific experiments, where they enhance operational accuracy and technical comprehension. To achieve synchronized swarm control, the proposed system employs a modular design approach, enabling each robot to operate as an independently controlled unit, while coordinated path design facilitates the collective movement of multiple robots. The hardware architecture integrates a positioning camera, a probe-based motion structure, and a power-drive circuit, while the software framework incorporates machine vision for positioning and pose recognition, a path navigation system, and Wi-Fi communication. This integrated approach equips the micro-robots with precise tracking and path-planning capabilities, ensuring the efficient execution of specified path trajectories. © 2024 IEEE.

关键词： Microrobots

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DRL-SLAM: Enhanced Object Detection Fusion with Improved YOLOv8 6th

DRL-SLAM: Enhanced Object Detection Fusion with Improved YO...

引用

6th IFIP TC 12 international conference on Intelligence science, ICIS 2024

作者： Usman, Farooq Shi, Chaoxia Wang, Yanqing Nanjing University of Science and Technology Nanjing210094 China Nanjing Xiaozhuang University Nanjing211171 China

ISBN: (纸本)9783031712524

Simultaneous Localization and Mapping (SLAM) technologies are pivotal in advancing robotics and autonomous navigation, particularly within challenging indoor environments. These systems face significant challenges due to dynamic variables such as fluctuating lighting, occlusions, and the presence of moving objects. In response, this paper introduces a novel integration of Deep Reinforcement Learning (DRL) with the advanced object detection capabilities of YOLOv8 within a SLAM framework, termed DRL-SLAM YOLOv8. This integration enhances object detection by leveraging DRL’s ability to learn from environmental interactions and YOLOv8’s precise and efficient real-time object recognition. Our experiments demonstrate the superiority of DRL-SLAM YOLOv8 over traditional methods, with marked improvements in detection accuracy and system reliability under diverse conditions. Notably, our approach significantly improves navigational effectiveness, as evidenced by increased distance coverage and goal achievement compared to standard SLAM techniques, validating its potential in real-world applications. © IFIP international Federation for Information Processing 2025.

关键词： SLAM robotics

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Enhancing Bus Number Detection Efficiency with Transfer Learning and Fine-Tuned Optical Character Recognition 1

Enhancing Bus Number Detection Efficiency with Transfer Lear...

引用

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

作者： Arifando, Rio Eto, Shinji Wada, Chikamune Kyushu Institute of Technology Graduate School of Life Science and Systems Engineering Fukuoka Japan

ISBN: (纸本)9798350348842

This research investigates two crucial aspects of computer vision and object recognition, with implications for real-world applications, specifically in bus detection and bus number recognition. The first aspect focuses on enhancing the efficiency and accuracy of bus detection using Transfer Learning with Frozen Layers (TLFL), particularly emphasizing the YOLOv5n model. TLFL selectively adapts a pre-Trained neural network, preserving low-level features while fine-Tuning domain-specific components, significantly improving training speed and performance. It outperforms the baseline YOLOv5n model with fewer training epochs, highlighting the importance of balancing existing knowledge and domain-specific adaptation. The second aspect explores Optical Character Recognition (OCR) models for bus number recognition. Customization and fine-Tuning, as seen in the transformation of Paddle OCR to Fine-Tuning Paddle OCR, substantially increase prediction confidence and reduce Character Error Rate (CER). This fine-Tuning process enhances OCR adaptability and precision, especially in challenging scenarios like accurate bus number recognition. A comparative analysis of OCR models shows the superiority of Fine-Tuning Paddle OCR, offering a balance between accuracy and efficiency, while other models present varying trade-offs between precision and speed. © 2024 IEEE.

关键词： Buses

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Role of RPA to Seize Opportunities in 5G Edge Computing in Telecommunications

Role of RPA to Seize Opportunities in 5G Edge Computing in T...

引用

2024 international conference on advances in Computing Research on science engineering and technology, ACROSET 2024

作者： Yendluri, Dileep Kumar Tatikonda, Reshmi Tatikonda, Ramya Ponnala, Jainath Kempanna, M. Bhuvanesh, A. University of the Cumberlands Department of Computer Science Williamsburg United States University of the Central Missouri Department of Computer Information Systems Warrensburg United States University of the Cumberlands Department of Information Technology Williamsburg United States Jawaharlal Technological University Department of Electronics and Communication Engineering Hyderabad India Bangalore Institute of Technology Department of Ai and Ml Bangalore India Psn College of Engineering and Technology Department of Electrical and Electronics Engineering Tirunelveli India

ISBN: (纸本)9798350388800

This paper explores the role of Robotic Process Automation (RPA) in leveraging opportunities presented by 5G edge computing in the telecommunications industry. Integrating RPA and 5G edge computing offers numerous benefits, including enhanced operational efficiency, real-time decision-making, improved service delivery, and cost savings. However, it also poses challenges such as complex integration, security concerns, and the need for effective change management. The paper comprehensively analyzes the potential benefits, challenges, and recommendations for implementing RPA in 5G edge computing. It explores use cases, future advancements, emerging technologies, and anticipated opportunities and challenges. The findings highlight the need for clear objectives, process optimization, collaboration between IT and business teams, and continuous monitoring to leverage RPA in 5G edge computing effectively. © 2024 IEEE.

关键词： Telecommunication industry

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ConciseNet: A Robust Model for Enhancing Signal Reconstruction in Wireless Sensor Networks 4

ConciseNet: A Robust Model for Enhancing Signal Reconstructi...

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4th international conference on advances in Electrical, Computing, Communication and Sustainable Technologies, ICAECT 2024

作者： Kumari, P. Meena Sekar, K. Jagadeesh, P. Dheepa, T. Avn Institute of Engineering and Technology Department of Computer Science and Engineering Telangana Hyderabad India National Institute of Technology Silchar Department of Computer Science and Engineering Assam Silchar India Barath University Department of Computer Science and Engineering Tamilnadu India Kongunadu College of Engineering and Technology Department of Computer Science and Engineering Tiruchirappalli India

ISBN: (纸本)9798350343670

This paper introduces a novel data collection model called ConciseNet that leverages a cutting-edge data reconstruction method to significantly enhance signal reconstruction accuracy in wireless sensor networks (WSNs). In traditional WSNs, data collection is prone to errors and losses, especially in long-range scenarios. The proposed model addresses this challenge by employing ConciseNet, an attentive sequential model that effectively compresses sensor signals without compromising information fidelity. The unique strength of ConciseNet lies in its ability to capture essential features from raw sensor data, allowing for efficient and precise reconstruction over extended periods. The result is a more robust and accurate representation of collected data, thereby improving the quality of information gathered by the WSN and maximizing the lifetime of sensors and WSNs. © 2024 IEEE.

关键词： Compressive sensing Data Reconstruction Time dependency Transformer Neural Network Wireless Sensor Network

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