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

共 47866 条记录，以下是1391-1400 订阅

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Body Partition Refinement Dynamic Graph Convolutional Network for Skeleton-based Action Recognition 4

Body Partition Refinement Dynamic Graph Convolutional Networ...

引用

4th international conference on Industrial Automation, robotics and Control engineering, IARCE 2024

作者： Liu, Wenkang Wang, Yifan Zhang, Xiaoheng Li, Yang Beihang University Department of Automation Science and Electrical Engineering Beijing China

ISBN: (纸本)9798350380323

Graph convolutional networks (GCNs) are the most commonly used methods recently and have greatly pro-moted research on skeleton-based action recognition. Aggregating features guided by a topology graph and generating adja-cency matrices with semantic edges in the topology graph are important for the task. However, building a simple and applica-ble graph is a challenging problem. In this work, we construct a novel body partition refinement dynamic graph convolutional network (BPR-DGCN) for skeleton-based action recognition, in which we propose a new body partition refinement dynamic graph convolutional module (BPR-DGCM) to efficiently extract representative features. Furthermore, by combining the traditional physical connection graph with our proposed body partition connection graph, we construct a body partition refinement dynamic graph convolutional unit (BPR-DGCU), which adopts a channel grouping strategy to learn a shared dynamic topology graph as a generic prior for all groups and refine it with chan-nel-specific body partition connection graph for different groups. Our BPR-DGCN outperforms state-of-the-art methods on the NTU RGB+D 60 dataset. © 2024 IEEE.

关键词： Musculoskeletal system

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Enhancing Lifting Efficiency with a Novel Lower-Limb Exosuit

Enhancing Lifting Efficiency with a Novel Lower-Limb Exosuit

引用

2024 international conference on Advanced robotics and Intelligent Systems, ARIS 2024

作者： Chen, Yu-An Toh, Fuh-Lian Chu, Ko-An Sebastian, Hans Chang, Biing-Chwen National Taiwan University Department of Mechanical Engineering Taipei10617 Taiwan National Taiwan University of Science and Technology Department of Mechanical Engineering Taipei106335 Taiwan

ISBN: (纸本)9798350362572

Lifting heavy loads has long posed significant risks, such as lower back pain and injuries due to high compressive forces. To address these challenges, we propose an innovative lower-limb exosuit that integrates both passive and active components, designed to optimize lifting performance while ensuring user comfort and safety. This study evaluates the exosuit's effectiveness in reducing muscle activation and altering the range of motion during squat lifting tasks. Our exosuit leverages a spherical scissor linkage mechanism and elastic bands for hip support, and extension springs for knee support. Experimental evaluation using electromyography (EMG) and motion capture data reveals significant reductions in muscle activity for the rectus femoris and gluteus medius, particularly in the latter, with reductions of 34.6% and 63.2%, respectively. Additionally, substantial changes in joint flexion angles, especially at the ankle were ob. These findings highlight the exosuit's potential to mitigate physical strain and enhance lifting efficiency, paving the way for advancements in assistive technologies for lifting assistance. © 2024 IEEE.

关键词： Electromyography

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AMR Navigation Based on Dynamic Control Sampling Space

AMR Navigation Based on Dynamic Control Sampling Space

引用

2023 international conference on advances in Electronics, Control and Communication Systems, ICAECCS 2023

作者： Bouraine, Sara Hasani, Idriss Djoudi, Alla Gourine, Ahmed Kazed, Boualem Center for Development of Advanced Technologies Division Robotics and Industrial Automation Baba Hassen Algeria University BLIDA-1 Electronic and Automation Department Blida Algeria University of Science and Technology Houari Boumedienne Bab ezzouar Algeria

ISBN: (纸本)9781665463102

This paper addresses the problem of local navigation for autonomous mobile robots in partially observable dynamic environments. The main contribution of this work is the expansion of a sampling based approach to deal with the robot and environment dynamic constraints and integrate a safety distance to keep the robot away from collisions. The developed algorithm has been implemented on a robotic platform with a Robot Operating System based embedded architecture, where it has been tested and validated in an indoor environment. © 2023 IEEE.

关键词： Navigation

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Fractional Kelvin-Voigt based Viscoelastic Control for self-Balancing Exoskeleton

Fractional Kelvin-Voigt based Viscoelastic Control for self-...

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2023 IEEE international conference on robotics and Biomimetics, ROBIO 2023

作者： Li, Wentao Li, Feng Yang, Ming Li, Jinke Li, Ming Zhu, Yuanpei Yin, Meng Tian, Dingkui Wu, Xinyu Southern University of Science and Technology Department of Electronic and Electrical Engineering Shenzhen518055 China Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen518005 China Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen518005 China University of Science and Technology of China Hefei230026 China

ISBN: (纸本)9798350325706

Self-balancing exoskeleton robots enable hands-free walking for the wearer, and the problem of its stable walking has been a challenge. In this paper, to achieve compliant and stable walking of a self-balancing exoskeleton robot and reduce the shock between the robot and the ground, we propose a new fractional kelvin voigt viscoelastic controller (FKVC). The proposed FKVC incorporates the advantages of fractional order and the kelvin voigt viscoelastic to endow the self-balancing exoskeleton with stable and dynamic walking capabilities. Simulation results show that the actual CoM position of the exoskeleton well tracks the reference CoM position, and the actual ZMP converges to the reference ZMP position. The ZMP is always within the effective support region of the biped. Therefore, we experimentally proved the practicality and effectiveness of the FKVC method, and the self-balancing exoskeleton successfully realizes stable dynamic walking. © 2023 IEEE.

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Assessing the Applicability of Adversarial Machine Learning Approaches for Cybersecurity 2

Assessing the Applicability of Adversarial Machine Learning ...

引用

2nd international conference on advances in Computation, Communication and Information technology, ICAICCIT 2024

作者： Takkalapally, Prashamsh Sharma, Nandan Jaggi, Arjun Hudani, Karim Gupta, Ketan Natarajan, Yuvaraj Department of Engineering Computing and Mathematical Sciences Lewis University United States Senior Security Analyst BC Public Service VictoriaBC Canada HCLTech San DiegoCA United States Tampa FL United States Dept. of Information Technology University of The Cumberlands WilliamsburgKY United States Department of Computer Science Engineering Sri Shakthi institute of engineering and technology Tamil Nadu Coimbatore India

ISBN: (纸本)9798331541217

Adverse machine learning (AML) is a rising area of study that uses system-mastering algorithms to perceive malicious hobbies or to discover malicious adversaries in cybersecurity settings. This research domain combines device-gaining knowledge with game principles to assess and expect the behavior of adversaries. This paper discusses the capacity of using AML tactics for cybersecurity and provides an overview of existing research study findings and safety literature to help the dialogue. Specifically, the paper investigates the security challenges posed by using AML techniques, together with the technical regulations and pointers, to ensure their relaxed and effective deployment. Moreover, the paper offers recommendations and future instructions for furthering studies on AML in cybersecurity. Typical, the evaluation highlights the significance of assessing the applicability of AML techniques for security applications, in addition to its capability to enhance the effectiveness of security systems. © 2024 IEEE.

关键词： Adversarial machine learning

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Optimization of Microbial Fuel Cells: Enhancing Electrical Output Through Gradient-Based Optimization 6

Optimization of Microbial Fuel Cells: Enhancing Electrical O...

引用

6th international conference on robotics and Automation in Industry, ICRAI 2024

作者： Mehmood, Hassan Zafar, Tayyab Kamal, Khurram Aun Rizvi, Syed Muhammad Ratlamwala, Tahir National University of Sciences and Technology Department of Mechatronics Engineering Islamabad Pakistan Department of Engineering Science Islamabad Pakistan

ISBN: (纸本)9798350355703

Microbial Fuel Cells (MFCs) are environment-friendly devices to generate energy through microbial metabolism of the chemical energy of organic compounds. Few of the critical challenges of implementing MFCs are their low power density, high internal resistance, and poor electron transport. These factors are major drawbacks to the MFCs efficiency and ability to scale up MFCs. The proposed work aims to enhance the MFC performance by optimizing the proportions of key operational parameters to overcome the implementation challenges. These parameters include Substrate Concentration (S), Anodophilic Biomass (xa), Methanogenic Biomass (x/m), and Oxidized Mediator (M/ox). The parameters are optimized using a Gradient Based Optimization (GBO). During the optimization process, it was imperative to establish a sound mathematical model that predicted MFC's biological and physical behavior. With the implementation of the GBO algorithm, the output current is enhanced by 8. 89 percent. The results shows that promising future of the proposed method. © 2024 IEEE.

关键词： Anodophilic Biomass Bioelectrochemical Systems Gradient-Based Optimization Methanogenic Biomass Microbial Fuel Cells Oxidized Mediator Substrate Concentration Sustainable Energy

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An Overview of Deployment of Information and Communications technology (ICT) in Disaster Risk Management

An Overview of Deployment of Information and Communications ...

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

作者： Nachappa, M.N. Sharma, Himanshu Pal, Ritu Department of Computer Science and Information Technology Bangalore India Noida Institute of Engineering and Technology Department of Electronics and Communication Engineering Uttar Pradesh Greater Noida India Tula's Institute Department of Computer Science and Engineering Dehradun India

ISBN: (纸本)9798350344387

Efficient disaster management necessitates the prompt and timely distribution of information to provide quick provision of emergency assistance to the affected population. The rapid growth of "information and communication technologies"has made it easy to acquire real-time information from many sources. The utilization of ICT in many phases of disaster management is being examined. The analysis includes an examination of current solutions as well as an investigation into the integration of developing ICT networks, services, and applications. Various evacuation techniques are being examined. Following a comparison of various ICT-based technologies, a model for evacuation is proposed. © 2023 IEEE.

关键词： Disaster Management Early warning systems ICT Remote sensing Risk

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Advantages and Challenges of Utilizing RFID technology 15

Advantages and Challenges of Utilizing RFID Technology

引用

15th international conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Dhabliya, Dharmesh Amudha, A. Kaur, Ashmeet Gayathri, C. Garg, Anvesha Vivek, V. Vishwakarma Institute of Information Technology Department of Information Technology Maharashtra Pune India Karpagam Academy of Higher Education Department of Electrical and Electronics Engineering Coimbatore641021 India Research Impact and Outcome Chitkara University Centre of Rajpura Punjab 140417 India Prince Shri Venkateshwara Padmavathy Engineering College Department of Science and Humanities Chennai127 India Quantum University Research Center Quantum University India School of Engineering and Technology Computer Science and Engineering Karnataka Bangalore India

ISBN: (纸本)9798350370249

Radio Frequency identity (RFID) is a rising technology that uses radio waves to become aware of and tune gadgets. With advances in hardware and software, RFID technology gives many blessings to agencies by means of growing facts accuracy, improving asset tracking, inventory management, and different procedure automation. However, no matter the diverse blessings it could provide, there are several challenges that businesses have to consider while implementing the RFID era. Those demanding situations encompass capability security and privacy worries, technical complexity, price, and interference from other RF indicators. To capitalize on the advantages of RFID, agencies must carefully weigh the advantages against the potential risks to decide the end goals and whether RFID is the most viable solution. © 2024 IEEE.

关键词： Accuracy Advantages Agencies Automation Demanding Implementing Improving Indicators

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Effective Control of Unmanned Aerial Vehicles Based on Reward Shaping 6

Effective Control of Unmanned Aerial Vehicles Based on Rewar...

引用

6th international conference on robotics, Control and Automation engineering, RCAE 2023

作者： Kong, Shengqi Li, Minne Zhou, Yuan Wang, Zhiyuan College of Computer Science and Technology National University of Defense Technology Changsha China Intelligent Game and Decision Lab IGDL Beijing China

ISBN: (纸本)9798350315301

The autonomous control of unmanned aerial vehicles (UAVs) presents a challenging problem in the field of control. Conventional autopilot designs utilize single-input, single-output (SISO) controllers, such as PID controllers, which may become unstable under certain conditions. To overcome these limitations, researchers have explored the use of reinforcement learning (RL) algorithms in UAV control. This paper reviews related works in the field and proposes a study to evaluate the impact of shaping rewards based on aircraft attitude on the effectiveness of UAV control. We investigated the application of reinforcement learning in UAV control, specifically focusing on the impact of shaping rewards based on aircraft attitude in variable wind speed environments. Two experiments were conducted to investigate the training rate and control effectiveness of agents with shaping rewards and non-shaping rewards. The findings indicate that shaping rewards based on flight attitude effectively reduce turbulence in the aircraft's flight process and outperform non-shaping rewards in altitude and heading control in the Gaussian wind speed model. © 2023 IEEE.

关键词： Fixed wings

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Research on Soft Sensor Modeling of Support Vector Machine for Wastewater Treatment 8

Research on Soft Sensor Modeling of Support Vector Machine f...

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8th international conference on Automation, Control and robotics engineering, CACRE 2023

作者： Li, Mingzhu Cheng, Hongchao Wang, Xiaojuan Qin, Jiaxian Haikou University of Economics TJ-YZ School of Network Science Haikou China Guangdong Polytechnic Normal University School of Automation Guangzhou China Hainan College of Economics and Business School of Electromechanical and Automotive Engineering Haikou China

ISBN: (纸本)9798350302776

To improve the prediction accuracy of water quality indexes such as BOD (Biochemical Oxygen Demand) in wastewater treatment process, a novel soft sensor modeling method based on support vector machine (SVM) is designed. The Gaussian kernel function is configured for the proposed method, and the grid search method is combined with K-fold cross-validation to search the optimal values of Gamma and C parameters, thereby improving the prediction accuracy of the proposed model. Finally, the method is tested by using the production data of wastewater treatment. The experimental results show that the proposed model has high prediction accuracy, which provides an effective method for guiding practical production. © 2023 IEEE.

关键词： Wastewater treatment

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