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检索条件"任意字段=5th International Conference on Robotics and Automation Systems, Robotics 2010"

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Design and PID Control of a Lower Limb Exoskeleton for Virtual Reality-Based Telerehabilitation 11

Design and PID Control of a Lower Limb Exoskeleton for Virtu...

引用

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

作者： Aktan, Mehmet Emin Falkowski, Piotr Zawalski, Krzysztof Jeznach, Kajetan Ömürlü, Vasfi Emre Akdoǧan, Erhan Bartin University Department of Mechatronics Engineering Bartin Turkey Health Institutes of Türkiye Istanbul Turkey Industrial Research Institute for Automation and Measurements Piap Lukasiewicz Research Network Warsaw Poland Yildiz Technical University Department of Mechatronics Engineering Istanbul Turkey

ISBN: (纸本)9798331509293

Rehabilitation is a critical process that enables people who have lost motor skills to regain their physical abilities. Exoskeletons offer innovative solutions to accelerate the functional recovery of patients and increase the effectiveness of treatment. the integration of virtual reality and biological signal processing technologies into such systems allows the user's movements to be detected in real time with high accuracy, enabling remote and personalised treatment. this study explains the working principle and control structure of a 4-degree-of-freedom lower limb exoskeleton robot developed for virtual reality-based telerehabilitation. the details of the electrical components of the system such as controller, input and output units, motor, sensor, virtual reality goggles, EEG and EMG devices and their interrelationships are explained. the position control performance for each joint using the PID control method is analysed. the results show that the exoskeleton can follow the given target trajectories with different error values depending on the period and joint. A maximum position error of 0.659 degrees was observed in the hip flexion-extension joint, while the average error for this joint was recorded as 0.385 degrees. © 2025 IEEE.

关键词： Functional neural stimulation

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Unfolding Finance 4.0 through Digital Innovation and Financial automation

Unfolding Finance 4.0 through Digital Innovation and Financi...

引用

Advances in Computing, Communication Control and Networking (ICAC3N), international conference on

作者： Ardhendu Shekhar Singh Deepa Pillai Adesh Doifode Trupti Bhosale Symbiosis School of Banking and Finance Symbiosis International (Deemed University) Pune India

ISBN: (数字)9798350330861

ISBN: (纸本)9798350330878

the financial services sector in India has leveraged the power of Industry 4.0 extensively on account of digital innovation and automation of financial processes. the rising competition in the financial services sector has compelled financial institutions to create value for their customers through new service offerings. To participate and prosper in the challenging business environment, traditional banks have to build new value propositions and business models for a leading edge. Digital technologies such as the cloud, the Internet of things (IoT), analytics, automation, robotics, and artificial intelligence are the enablers of transformation in financial services. Fintech innovations coupled with mass personalisation and product customisation have led financial institutions to embark on the adoption of technology-led change. the paper aims to study the adoption of digital technologies by financial institutions to expand their scope and outreach of personalised services to enhance customer value.

关键词： Product customization Technological innovation Cloud computing Finance Security Internet of things Artificial intelligence

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Submarine Cable Detection Based on LSR and Image Clustering

Submarine Cable Detection Based on LSR and Image Clustering

引用

Computer Vision, Image and Deep Learning (CVIDL), international conference on

作者： Siquan Yu Wentao Li Liheng Zhang State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Shenyang China

ISBN: (数字)9798350373820

ISBN: (纸本)9798350373837

Submarine cable is an important carrier for intercontinental communication. Due to the unique nature of the usage environment, submarine cables require regular inspections to ensure normal operation. Usually, there are three methods used for underwater cable detection, including divers, fish towing, and cable robots. the drawbacks of these inspection methods include the need for a large amount of manpower, material resources, and financial resources. Because the depth of the operation is limited, with potential personnel risks. the limited detection range is not suitable for large-scale inspections and other issues. In order to solve the problems, autonomous underwater vehicles (AUVs) become popular tools to detect submarine cable. AUVs carry various detection equipment to achieve rough and precise exploration of submarine cables. Due to the weak impact of sea conditions on underwater operations, AUVs inspection of submarine cable can be suitable for the vast majority of scenarios. they can not only discover submarine cable on a large scale, but also can closely track and detect submarine cable. this paper proposes a method for AUV to autonomously identify submarine cable. Specifically, the proposed method uses Gabor filter to filter side scan sonar (SSS) images, and designs a scoring mechanism to select the corresponding largest image block as a suspected submarine cable. the submarine cable is determined using image clustering and position prior. In this paper, we conduct extemsive experiments to verify the effectiveness of the proposed algorithm.

关键词： Underwater cables Optical filters Meters Autonomous underwater vehicles Machine learning algorithms Clustering algorithms Sonar

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Simulation of Liquid Level Cascade Control System Based on Genetic Fuzzy PID

Simulation of Liquid Level Cascade Control System Based on G...

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robotics, Control and automation Engineering (RCAE), international conference on

作者： Jizhi Mao Zhijia Yang Shusheng Zhang College of Automation and Electrical Engineering Shenyang Ligong University Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China

ISBN: (数字)9781665459419

ISBN: (纸本)9781665459426

the model design and basic principle of liquid level control system are described. In order to improve the dynamic response of liquid level control, the overshoot and steady-state error accuracy of the system are improved. In this paper, we apply the conventional PID controller to the single-loop system and the cascade system respectively, and introduce the fuzzy control algorithm based on the conventional PID control algorithm to design a cascade parameter self-adjusting fuzzy PID controller, then use genetic algorithm to optimize fuzzy control rules to generate genetic fuzzy PID controller. the MATLAB/Simulink simulation results show that, compared with the traditional PID control, the genetic fuzzy PID control has better control effect and anti-interference ability, and has good control performance.

关键词： Fuzzy control PI control Liquids automation Heuristic algorithms Transfer functions Genetics

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IoT and AI Synergy in Society: robotics and automation Perspectives

IoT and AI Synergy in Society: Robotics and Automation Persp...

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international conference on Contemporary Computing and Informatics (IC3I)

作者： B.T. Geetha J. Salomi Backia Jothi Shaunak Pal Imam Taqi Deen Islam K. S. Raghuram Mukesh Soni Department of ECE Saveetha School of Engineering SIMATS Saveetha University Tamil Nadu India Department of Commerce Faculty of Science and Humanities SRM Institute of Science and Technology Ramapuram campus Chennai School of Computer Science and Engineering Vellore Institute of Technology Vellore Tamil Nadu India University of Electrical Science and Technology of China Chengdu Sichuan China Department of Mechanical Engineering Vignan’s Institute of Information Technology (A) Visakhapatnam Dr. D. Y. Patil Vidyapeeth Pune Dr. D. Y. Patil School of Science& Technology Tathawade Pune

ISBN: (数字)9798350350067

ISBN: (纸本)9798350350074

the Internet of things, or IoT, is a relatively new Internet revolution that is being successfully adopted by the corporate, industrial, healthcare, and economic sectors as well as other areas of the modern information society. Specifically, IoT with artificial intelligence (AI) support improves a great deal the performance in a wide range of daily applications with a focus on automation systems, robotics, transportation, and business. Smart automation in the manufacturing sector is now possible thanks to the development of Industry 4.0. the BRDT algorithm is used in this work to track how much energy appliances and machinery use, forecast behaviour, and identifies unusual conduct. When the suggested system’s efficiency is compared to current approaches, it provides an efficiency of $\mathbf{8 5 \%}$. the application of this technology raises a number of standardisation, security, resource planning, legal, and paradigm-shifting business challenge problems. the whole supply chain and all of its actors, from producers to end users, are crucial to the success or failure of Industry 4.0 deployment.

关键词： Service robots Supply chains Transportation Medical services Fourth Industrial Revolution Planning Internet of things Security Machinery Business

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conference Committee

Conference Committee

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international conference on robotics and automation Sciences (ICRAS)

Provides a listing of current committee members and society officers.

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Enhanced Streetlight Management: Using IoT and ESP32 for Automated Fault Detection

Enhanced Streetlight Management: Using IoT and ESP32 for Aut...

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India Council international Subsections conference (INDISCON), IEEE

作者： Swati Bhisikar Prabodh Jagtap Shilpa Sonawane Hrushikesh Sawant Prerana Pisal Dept. of Electronics and Telecommunication Rajarshi Shahu College of Engineering Pune India Dept. of Information Technology Vishwakarma Institute of Information Technology Pune India Dept. of Automation and Robotics Rajarshi Shahu College of Engineering Pune India

ISBN: (数字)9798350376753

ISBN: (纸本)9798350376760

the core focus of this paper is to implement a cutting-edge system for intelligent streetlight management, leveraging an automotive monitoring system to identify and rectify any faults within the streetlight infrastructure. Rapid response of the proposed fault detection system will help save the time of the linemen, which is wasted in manually detecting the faults at streetlights, and will help to reduce the workload of the linemen. Also, most of the time, the detection of the problem mainly depends on the grievances of the local people. thus, this causes delays in the maintenance of the streetlights, wastage of power, and problems for the local people. So, to reduce such problems, we have developed an automatic detection system for streetlight faults. During nighttime, this system will detect faults such as whether the lamp is ON or OFF, or if a wire cut is in the circuit. As the fault is detected, the information will be provided to the authorized person; the information will contain the type of fault that occurred in the streetlight system.

关键词： Smart cities Local government Fault detection Light emitting diodes Maintenance Circuit faults Wire Internet of things Monitoring Intelligent sensors

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Improved YOLOv5s Network for Traffic Object Detection with Complex Road Scenes

Improved YOLOv5s Network for Traffic Object Detection with C...

引用

IEEE international conference on Cyber Technology in automation, Control, and Intelligent systems

作者： Yi Cao Yuning Wang Huijie Fan Faculty of Vehicle Engineering and Mechanics Dalian University of Technology Da Lian China Unit 32681 PLA Tieling China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China

Aiming at the problems of low target detection accuracy and prone to false detection and missed detection in complex traffic scenes, a road target detection algorithm based on improved YOLOv5s is proposed. Firstly, a feature extraction layer based on Spatial Pyramid Pooling(SPP) is adopted for increasing shallow feature receptive fields named as Multi-scale SPP module (M-SPP). M-SPP is designed to fully integrate feature information of different scales for improving feature extraction ability of our network. Secondly, a Global Context Attention Module(GCAM) is proposed, in focusing on important features in channel and spatial dimensions, allowing the network to focus on more useful information. Finally, experimental results show that detection accuracy of the improved YOLOv5s model we proposed on the UA-DETRAC dataset, compared with the original algorithm, improved by 1.83% and 2.54% respectively. Our improved model abtain good detection accuracy while ensuring real-time performance, and solves problem of missed detection and false detection of small targets in complex road scenes to a certain extent.

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Semantic Map Construction Method Based on Brain-Inspired SLAM

Semantic Map Construction Method Based on Brain-Inspired SLA...

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IEEE international conference on Cyber Technology in automation, Control, and Intelligent systems

作者： Hangpiao Zhao Fengzhen Tang The State Key Laboratory of Robotics Shenyang Institute of Automation Shenyang China The University of Chinese Academy of Sciences Shenyang Institute of Automation Beijing China

ISBN: (数字)9798331506056

ISBN: (纸本)9798331506063

Simultaneous localization and mapping (SLAM) is one of the core techniques for robots to move autonomously in unknown environments. Rat-SLAM, inspired by the navigation mechanism of the animal brain, provided nice performance in many environments. However, the experience map constructed by RatSLAM excluded semantic information, which is considered to play an important role in human environmental cognition and spatial navigation. In this paper, we propose a method to construct semantic experience map, combining the state-of-the-art deep neural network and RatSLAM. In our method, YOLOv5 is utilized to extract semantic information from the environmental images. the information of static objects, such as road signs, is selected to be incorporated into the experience map, being more closely to the brain navigation. To avoid the same object being repeatedly marked, we propose a semantic dynamic island mechanism, which only marks the center of the island in the experience map. the proposed method is verified on KITTI datasets, showing that it can successfully realize the construction of semantic experience map. the semantic experience maps are more intuitive and understandable by human, facilitating human-robot interaction, i. e. helping robots to fulfil more complex tasks for human.

关键词： YOLO Simultaneous localization and mapping Navigation Roads Semantics Human-robot interaction Detectors Data mining Intelligent systems Robots

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RDDS: Road Disease Detection Model Based on YOLOv5

RDDS: Road Disease Detection Model Based on YOLOv5

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IEEE international conference on Cyber Technology in automation, Control, and Intelligent systems

作者： Zhiqiang Han Jun Gong Yu Qiao School of Vehicle and Transportation Engineering Taiyuan University of Science and Technology Taiyuan China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China

ISBN: (数字)9798331506056

ISBN: (纸本)9798331506063

the utilization of intelligent vehicles for detecting road anomalies has become a relatively common phenomenon. the existing road disease detection workload is large, the robustness is not high, and small diseases are easily ignored, which brings huge challenges to road disease detection. A road disease detection model named RDDS based on YOLOv5 is proposed. Based on the YOLOv5 algorithm, we incorporate Transformer encoder blocks into the head part to form Transformer Prediction Heads (TFE), expanding their number to four. this enhancement aims to improve the model's capability to detect small targets and road diseases of different scales. In addition, we introduce the convolutional block attention model (CBAM) to make the network pay more attention to important channels and spatial locations, thereby improving the performance and generalization ability of the model. Aiming at the problems of low resolution and insufficient data volume in current road disease data sets, we propose a new road disease detection data set RDDSC. Finally, we conducted experiments on the RDDSC data set. the experimental results showed that compared with the original YOLOv5, the RDDS parameters increased slightly, while the detection accuracy was significantly improved. Compared with existing detection algorithms, RDDS has obvious advantages in road disease detection.

关键词： YOLO Accuracy Roads Predictive models Transformers Prediction algorithms Robustness Maintenance Spatial resolution Diseases

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