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检索条件"任意字段=IEEE International Conference on Cyber Technology in Automation,Control,and Intelligent Systems"

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Push-Assisted Functional Grasping Method Based on Prioritized Experience Replay in Clutter

Push-Assisted Functional Grasping Method Based on Prioritize...

引用

ieee international conference on cyber technology in automation, control, and intelligent systems

作者： Fei Wang Manyi Shi Chao Chen Jinbiao Zhu Xinyao Wang Department of Robot Science and Engineering Northeastern University University Shenyang Liaoning Province China

ISBN: (数字)9798331506056

ISBN: (纸本)9798331506063

In life service task scenarios, functional grasping is the basis for robots to perform other complex tasks. Through the exploration of the agent and the environment, we map the insights of local features to the global situation from the visual level, thereby achieving functional capture based on small sample priors. Let the agent's grasping strategy stably converge to the preset grasping posture. In addition, we use the grasp network to evaluate the effect of promoting the network, and use priority experience playback to focus on learning for experiences that have a significant auxiliary role. It can significantly improve the functional capture success rate and system action efficiency in clutter scenes.

关键词： Visualization automation Grasping Reinforcement learning control systems Clutter intelligent systems Robots

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2024 8th international conference on Robotics, control and automation, ICRCA 2024

2024 8th International Conference on Robotics, Control and A...

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8th international conference on Robotics, control and automation, ICRCA 2024

ISBN: (纸本)9798350344721

The proceedings contain 85 papers. The topics discussed include: a hybrid method for INS/GPS integrated navigation system based on the improved Karman filter and back propagation neural network;development of Simulink-based physical experiment platform for EtherCAT bipedal robots;a biogeography-based optimization algorithm with heuristics for distributed multiproduct scheduling problem;research on low energy consumption AC system control strategy of battery electric vehicles;flyback converter modeling and overload control characteristics for power supply based on state space averaging;a simple confidence-supervised model for high resolution defect recognition;research and development of intelligent warehouse management system based on RFID technology;research on methods of vehicle image retrieval in expressway scenarios based on deep learning neural network;and motion simulation control system of detecting robot based on digital twin.

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Macro-Mini Manipulator Based on Multi-Force Sensors for Force control Application

Macro-Mini Manipulator Based on Multi-Force Sensors for Forc...

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ieee international conference on cyber technology in automation, control, and intelligent systems

作者： Junjie Dai Chin-Yin Chen Han Chen Guilin Yang Zhejiang Key Laboratory of Robotics and Intelligent Manufacturing Equipment Technology Ningbo Institute of Materials Technology and Engineering Ningbo China University of Chinese Academy of Sciences Beijing China College of Mechanical Engineering Zhejiang University of Technology Hangzhou China

ISBN: (数字)9798331506056

ISBN: (纸本)9798331506063

In polishing, force-controlled performance is affected by manipulator dynamics, end-effector dynamics, and workpiece uncertainty. This paper proposes a new force-controlled method by utilizing multi-force sensors for robotic polishing applications. One of the force sensors is installed between the endpoint of the manipulator and the fixed platform of the end-effector to realize the dynamic decoupling. The other one is added at the back of the workpiece to realize force tracking. The experimental results indicate that the proposed method's contact force response speed and overshoot are both better than those of the conventional force-controlled method.

关键词： Uncertainty Force Dynamics Process control Robot sensing systems End effectors Force sensors Force control intelligent systems Manipulator dynamics

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GRU-Based Prediction of Muscle Activation Using IMU Data: Integrating VR for Rehabilitation Assessment

GRU-Based Prediction of Muscle Activation Using IMU Data: In...

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ieee international conference on cyber technology in automation, control, and intelligent systems

作者： Weishu Lin Chen Su Zida An Zhengyi Li Qi Jing Shengwei Zhang Fei Wang School of Robotics Northeastern University Shenyang Liaoning China School of Software Northeastern University Shenyang Liaoning China School of Robotics North-eastern University Shenyang Liaoning China

ISBN: (数字)9798331506056

ISBN: (纸本)9798331506063

In this paper, we propose a novel approach using IMU data to predict muscle activation, diverging from the conventional method of employing sEMG data for continuous angle estimation. We opt for Gated Recurrent Units (GRUs) over Long Short-Term Memory (LSTM) due to their simplified and efficient structure, achieving an accuracy of 0.7562 in predicting muscle activation. Additionally, we utilize VR to visualize the color changes in muscles, enhancing the effectiveness of rehabilitation assessments.

关键词： Accuracy automation Image color analysis Estimation Data visualization Muscles Logic gates control systems intelligent systems Long short term memory

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Lightweight intelligent Fire Monitoring System Based on Flask and YOLOv8 2

Lightweight Intelligent Fire Monitoring System Based on Flas...

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2nd international conference on Artificial Intelligence and automation control, AIAC 2024

作者： Zheng, Zhihong Cai, Xiangyu Wang, Hongjie Fu, Xiaoyang School of Computing Zhuhai College of Science and Technology Zhuhai China

ISBN: (纸本)9798331529147

In recent years, with the impact of global warming, the incidence of fire has increased, and the prevention and control of fire has become an important topic of safety management. Traditional fire alarm systems rely on temperature and smoke sensors, but they often experience delays, making early fire detection challenging. Based on this requirement, this system aims to realize real-time fire monitoring and provide more efficient early fire warning by introducing computer vision technology. The system uses the improved YOLOv8 lightweight model as the core fire detection algorithm, and realizes the front-end transmission and display of video streams through the Web service constructed by the lightweight Flask framework. The system includes three core modules: front-end page, back-end server and model reasoning, to realize the automation of the whole process from video capture, image analysis to result display. Compared with YOLOv8n, the recall rate of our model is increased by 1.9% and the mAP is increased by 0.5%, while the model size is reduced by 15.4% and the calculation amount is reduced by 21.0%. In general, the system has a lightweight structure and fast reasoning, which ensures the real-time response ability of the system, and is also convenient for flexible deployment on various hardware environments. © 2024 ieee.

关键词： Fire alarm systems

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Line Feature Based Visual Servo control with TDE for Underwater Vehicle Manipulator systems Target Grasping

Line Feature Based Visual Servo Control with TDE for Underwa...

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2024 ieee international conference on Unmanned systems, ICUS 2024

作者： Zhang, Yunfei Bian, Xinyu Sun, Yize Zhang, Zongyu Huang, Hai Yang, Xu National Key Laboratory of Autonomous Marine Vehicle Technology Harbin Engineering University Harbin China State Key Laboratory of Management and Control for Complex System Institute of Automation Chinese Academy of Sciences Beijing China

ISBN: (纸本)9798350384185

Underwater vehicle manipulator systems (UVMSs) is becoming a research hotspot in the field of marine intelligent equipment. Introducing visual feedback equipped with cameras in the loop to guide UVMS to complete the grasping has comprehensive advantages of response speed, work efficiency and intelligence. In this paper, mapping between the feature error and the motion of the UVMS generalized degrees of freedom is established to realize the suspended grasping under the coordinated motion of the vehicle body and the manipulator. Then, a UVMS motion control algorithm based on time delay estimation (TDE) is constructed for visual servo autonomous grasping process, the TDE of which is used to estimate and compensate the lumped interference in real time. The Lyapunov theory is applied to analyze its stability and its control performance is verified through simulation experiments. The simulation results shew the effectiveness of the proposed visual servo control with TED method based on line features. © 2024 ieee.

关键词： Visual servoing

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A Novel Hand Gesture Recognition Method Using sEMG-Based PSODE-BPNN 12

A Novel Hand Gesture Recognition Method Using sEMG-Based PSO...

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12th international conference on cyber technology in automation, control, and intelligent systems, cyber 2022

作者： Li, Ling-Long Cao, Guang-Zhong Zhang, Yue-Peng Chen, Jiang-Cheng College of Mechatronics and Control Engineering Shenzhen University Guangdong Key Laboratory of Electromagnetic Control and Intelligent Robots Shenzhen518060 China

ISBN: (数字)9781665472678

ISBN: (纸本)9781665472678

Aim to improve the deficiencies of slow convergence speed and prone to trapped into local minimum for back propagation neural network (BPNN) in sEMG-based hand gesture, a novel hand gesture recognition method associating particle swarm optimization (PSO) with differential evolution (DE) is proposed to optimize BPNN, namely PSODE-BPNN. Firstly, initial parameters of weights and biases are adjusted and updated to yield optimal values, via PSO and DE incorporation with the gradient descent method of BPNN. Secondly, the optimal values are utilized as the initial parameters to train the BPNN. Then the proposed method is evaluated on sEMG-based hand gesture dataset Ninapro DB4. The performance for the PSODE-BPNN is compared with the PSO-BPNN, the BPNN, and other related competing methods in literatures. The experimental results show that the PSODE-BPNN improves the inadequacy of slow convergence rate and local minimum of BPNN, and achieves higher gesture recognition accuracy than other comparison listed methods. The effectiveness and superiority of the proposed method is significantly validated. © 2022 ieee.

关键词： Optimal systems

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Truncated Predictor Feedback control for Linear systems with Multiple Distributed Input Delays

Truncated Predictor Feedback Control for Linear Systems with...

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ieee international conference on cyber technology in automation, control, and intelligent systems

作者： Guangjie Wang Qingsong Liu School of Information Science and Engineering Wuhan University of Science and Technology Wuhan China

This paper aims to deal with the delay compensation problem for linear systems in the presence of three distributed input delays. A fresh state variable is instituted so as to design the state-based feedback controllers. Whereafter, truncated predictor feedback (TPF) approaches are built to make up for the three distributed input delays. It is displayed that the original system possessing three distributed input delays can be stabilized via the TPF controller. Additionally to demonstrating the efficacy of the built controller via an example.

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FLDP: A differentiated privacy security approach based on flow model 3

FLDP: A differentiated privacy security approach based on fl...

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3rd ieee international conference on intelligent technology and Embedded systems, ICITES 2023

作者： Zhao, Xing Wang, Yongli Chen, Yuke Tian, Fengjun School of Cyber Science and Engineering Nanjing University of Science and Technology Nanjing China

ISBN: (纸本)9798350343755

Sensitive data in standard deep learning training can be subject to assaults. These attacks take advantage of the disclosure of gradients and intermediate representations during the training process, potentially resulting in data breaches and unauthorized access to sensitive information. Concerns about the privacy and security of sensitive data during the training process have grown in importance as deep learning has grown in popularity. This study describes a novel strategy FLDP for improving the privacy and security of deep learning training by combining differential privacy (DP) with stochastic gradient descent (SGD) and flow model. Our strategy improves privacy and security without compromising deep learning model training efficiency or scalability. Individual data points are indistinguishable in our methodology, reducing the danger of privacy *** of applying a consistent privacy level to all data points, our technique enables for privacy protection to be differentiated based on data sensitivity. This adaptive privacy approach promotes value while preserving the most sensitive data's privacy. © 2023 ieee.

关键词： Sensitive data

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Comparison of Machine Learning Models for Identifying Malicious URLs

Comparison of Machine Learning Models for Identifying Malici...

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2024 ieee international conference on Information technology, Electronics and intelligent Communication systems, ICITEICS 2024

作者： Karajgar, Manasi Dnyanesh Sawardekar, Sonali Khamankar, Seema Tiwari, Nalini Patil, Manjusha Borate, Vishal Kisan Mali, Yogesh Kisan Chaudhari, Ashvini D. y Patil College of Engineering Pune India Dr. D y Patil Institute of Technology Pune India ADYPUSoE Pune India Dr D y Patil College of Engineering & Innovation Pune India G.H Raisoni Institute of Engineering and Management Pune India Nmims Center for Distance & Online Education Pune India

ISBN: (纸本)9798350382693

Malicious URLs, posing threats such as phishing and malware, cause significant financial losses globally. Detecting these URLs automatically before users access them is essential for cyber security. This study explores various machine learning techniques to accurately identify malicious URLs. Decision trees, random forests, K-nearest neighbors (KNN), and naive Bayes models are assessed using a dataset containing over 700,000 URLs. Ensemble models like random forest and extra trees exhibit superior performance, achieving over 93% accuracy in distinguishing between benign and malicious URLs. However, class imbalance remains a challenge, with minority malicious types often exhibiting lower precision. Comparative analysis highlights the feasibility of employing ensemble machine learning for automated malicious URL detection. With adequate examples and feature engineering, tree-based models can effectively identify threats and bolster cyber defense. © 2024 ieee.

关键词： Phishing

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