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检索条件"任意字段=3rd International Conference on Intelligent Robotics and Control Engineering, IRCE 2020"

共 1403 条记录，以下是91-100 订阅

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Highly Sensitive Flexible Resistance Strain Sensor Based on PDMS and Silver Nanowire 3

Highly Sensitive Flexible Resistance Strain Sensor Based on ...

引用

3rd international conference on Computer, control and robotics, ICCCR 2023

作者： Sun, Weiming Liu, Mei Djoulde, Aristide Liu, Xinyue School of Mechatronic Engineering and Automation Shanghai University Shanghai Key Laboratory of Intelligent Manufacturing and Robotics Shanghai200444 China

ISBN: (纸本)9781665492126

Flexible sensing film has a broad application prospect in the fields of medicine, wearable electronic devices, complex environment sensing, and others. In this paper, dimethylsiloxane (PDMS) was used as a flexible substrate to prepare composite conductive films by covering silver nanowires (AgNWs) with specific lines on the substrate surface. The resistance change of the sensor is mainly caused by the change in the number of contact points between AgNWs on the film surface, which has higher linearity than the traditional resistance strain gauge. The sensor is very sensitive and has a very good measuring effect on the pressure of 0-6N and the micro-bending caused by 0-1N. Common sensors made of micro-nano materials are usually affected by transverse strain. The sensor in this experiment designs a special circuit structure, which can effectively avoid the lateral effect. The sensor also has the characteristic of self-recovery, which can achieve self-recovery under a certain degree of damage. It can be used to detect small changes in the skin. © 2023 IEEE.

关键词： Substrates

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Care Guard: Holistic Health Monitoring and Autonomous Care System 3

Care Guard: Holistic Health Monitoring and Autonomous Care S...

引用

3rd international conference on Applied Artificial Intelligence and Computing, ICAAIC 2024

作者： Deepthi, J. Dharani, N.P. Aswini, Somu Priya, Desingh Geetha Harsha, Kurra Mani Bhargav, Yandamuri Sri Surya Siva Sree Vidyanikethan Engineering College Electronics and Instrumentation Engineering Tirupati India Electronics and Communication Engineering Tirupati India

ISBN: (纸本)9798350375190

Care Guard: Holistic Health Monitoring and Autonomous Care System outlines a comprehensive system integrating various sensors, microcontrollers, and communication technologies to monitor health parameters and provide assistance. The system employs a 12V battery for energy supply and incorporates components for instance, a temperature sensor, pulse oximeter, RFID, touch sensor, Arduino MCU, air quality sensor, LCD (16x2 lines), motor drivers M1 and M2, WiFi, and IoT. The project aims to enhance healthcare by leveraging IoT and robotics technologies to create an intelligent health monitoring and assistance system. The system continuously monitors vital health parameters such as temperature and pulse oximetry, providing real-time data comment addressed for users via the LCD. Additionally, it utilizes RFID technology for patient identification and touch sensors for user interaction. Furthermore, the method incorporates an automatic nurse assistant robot, which utilizes motor drivers for locomotion and navigation. The robot assists users by providing reminders for medication intake, scheduling appointments, and offering guidance on health-related queries. The incorporation of WiFi and IoT enables remote monitoring and control of the system, allowing healthcare professionals to access patient data and provide timely assistance from anywhere. Overall, this project presents a comprehensive solution for health tracking and assistance, leveraging IoT, robotics, and sensor technologies to improve healthcare accessibility and quality. © 2024 IEEE.

关键词： Temperature sensors

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Variable Scale Gesture Recognition: A Dataset and Comprehensive Analysis 3

Variable Scale Gesture Recognition: A Dataset and Comprehens...

引用

3rd international conference on robotics, Automation and intelligent control, ICRAIC 2023

作者： Li, Zhaoyu Xu, Tao Yang, Xiaohui Sun, Jiahui Zhu, Guangze University of Jinan School of Information Science and Engineering Jinan China

ISBN: (纸本)9798350360813

Dynamic gesture recognition plays an important role in natural human-computer interaction. Gesture image sequences can express more complex interaction intentions. Currently, the majority of dynamic gesture recognition algorithms are trained using fixed-length gesture sequences. However, the rate, amplitude, and angle of gestures differ across individuals, which presents a challenge to the effectiveness of existing dynamic gesture recognition algorithms. To address this challenge, we propose a variable scale gesture dataset. This dataset contains six types of dynamic gestures with different sequence lengths. In the experiments, we utilized major algorithms, including Two-Stream, C3D, CRNN and I3D, to test and evaluate their performance. Although current algorithms have been able to achieve high recognition rates for fixed-length sequences, they are unable to directly recognize variable-length sequences. The dataset includes four types of static gestures that can be used for dynamic gesture keyframe recognition and start/stop frame determination. The dataset proposed in this paper is expected to advance research in variable scale gesture recognition. © 2023 IEEE.

关键词： Gesture recognition

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Probability-Based Ship Encounter Classification Using AIS Data 3

Probability-Based Ship Encounter Classification Using AIS Da...

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3rd international conference on Computer, control and robotics, ICCCR 2023

作者： Zhu, Mingda Tian, Weiwei Skulstad, Robert Zhang, Houxiang Li, Guoyuan Norwegian University of Science and Technology Department of Ocean Operations and Civil Engineering AalesundN-6025 Norway

ISBN: (纸本)9781665492126

With the rapid development of the maritime industry, the traffic density of waterways has expanded significantly. Rising concern about safety becomes an important driving factor for developing an intelligent decision support system. In order to enhance situation awareness, the classification of ship encounters is needed. Considering the importance of encounter classification to maritime safety, this paper proposes a novel framework for the real-time classification of encounter types based on Automatic Identification System (AIS) data. First, encounter types are categorized based on expertise;then, the important features are used to construct a probability-based model. After that, sensitivity analysis (SA) is utilized to optimize the probability-based model by means of optimal feature selections. Experiments are conducted using real AIS data collected at the ferry crossing in Oslofjord. Furthermore, through case studies of the ferry and crossing traffic, the method is proven to be promising in effectiveness. © 2023 IEEE.

关键词： Sensitivity analysis

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Hand Gesture Classification using sEMG Signals and Ensemble Learning 3

Hand Gesture Classification using sEMG Signals and Ensemble ...

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3rd IEEE international conference on intelligent Techniques in control, Optimization and Signal Processing, INCOS 2024

作者： Chandran, Ranjeesh R Devaraj, D. Ashok, Saurav Shaji, Donfred Saju, Sam K Adishankara Institute of Engineering and Technology Department of Robotics and Automation Kerala Kalady India Kalasalingam Academy of Research and Education Department of Electronics and Electrical Technology Tamil Nadu Srivilliputhur India Adishankara Inst. of Eng and Tech. Department of Robotics and Automation Kerala Kalady India

ISBN: (纸本)9798350361186

Electromyographic signals offer details on a muscle activity of a person. In the case of hand movements various combinations of forearm muscles must be activated in order to carry out each gesture, which results in unique electrical patterns. On the other hand, identifying the motion being executed is made possible by the examination of these patterns of muscle activation, which are captured by EMG signals. This article presents a novel implementation on hand gesture classification utilizing Electromyography (EMG) signals recorded through a MYO Thalmic bracelet. The dataset consists of raw data collected from 36 subjects, each executing a series of static hand gestures. The classification model employed for this study is an ensemble of decision trees, achieving an impressive validation accuracy of 98.0% and a test accuracy of 98.1 %. The article outlines the dataset details, recording methodology, and provides an in-depth analysis of the model architecture, hyperparameters, and training results. © 2024 IEEE.

关键词： Decision trees

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An intelligent anti detachment detection method for hip joint assisted exoskeleton robot 24

An intelligent anti detachment detection method for hip join...

引用

3rd international Symposium on control engineering and robotics, ISCER 2024

作者： Ning, Yeyan Xu, Jinxin Luo, Jinlong Liu, Jianwen Robot Center The 21st Research Institute of China Electronics Technology Group Corporation Shanghai60088063 China

ISBN: (纸本)9798400709951

The rapid development of cutting-edge technology continuously enhances the modernization level of intelligent equipment. Traditional exoskeleton robots often use fixed gait recognition for assistance, but their adaptability is limited, and it is easy to cause injury to the wearer when the binding falls off. This article first analyzes the overall structure of hip joint exoskeleton robots, and comprehensively obtains a feasible plan for anti detachment detection;Secondly, starting from analyzing the physiological structure of the human body and the mechanism of gait movement, based on joint degrees of freedom and motion orientation, the exoskeleton driving method is determined, and the torque changes of assistance under different gait are obtained as a reference for setting angle thresholds;Finally, an intelligent anti detachment detection algorithm for hip joint assisted exoskeleton robots is proposed, which uses key information such as angle threshold, step frequency size, and step frequency rate to make judgments. Adaptive recognition and learning memory recognition are integrated, and the effectiveness of the anti detachment detection algorithm is verified by reading the torque and current changes of the hip joint in the state of detachment. © 2024 ACM.

关键词： Exoskeleton (robotics)

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CR-GraspNet: A robust 6-DoF grasp generation method for cleaning robot 3

CR-GraspNet: A robust 6-DoF grasp generation method for clea...

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3rd international conference on control and intelligent robotics, ICCIR 2023

作者： Xinrui, Wang Lizhe, Qi Wenxuan, Jiang Yunquan, Sun Academy for Engineering and Technology Fudan University Shang Hai China

ISBN: (纸本)9781510671867

Operational cleaning robot face numerous challenges when attempting to deftly and steadily grasp objects in cluttered scenes due to factors such as limited areas, stacked items, and restricted sensor perception. To address this issue, we propose CR-Graspnet, a six-degree-of-freedom (6-DoF) grasp generation network that utilizes point cloud contact features. This approach decouples the grasp pose in high-dimensional space by defining contact points, allowing for joint learning of contact point sampling, grasp parameter regression, and grasp quality classification. Our experimental results demonstrate the effectiveness and feasibility of this method, with a success rate of 93% achieved in single target grasping scenarios. © 2023 SPIE.

关键词： Degrees of freedom (mechanics)

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Lower limb rehabilitation exoskeleton robots: A review of development directions 3

Lower limb rehabilitation exoskeleton robots: A review of de...

引用

3rd international conference on intelligent Mechanical and Human-Computer Interaction Technology, IHCIT 2024

作者： Ju, Yuanjie School of Technology Beijing Forestry University Beijing100083 China

ISBN: (纸本)9781510683105

In recent years, lower limb rehabilitation exoskeleton robots have been widely used in patients with lower limb movement disorders caused by neurological injuries and other disorders to provide long-lasting and standardized rehabilitation training assistance, and have therefore attracted the attention of the market and many researchers. Currently, the lower limb rehabilitation exoskeleton technology is relatively mature, but how to design more intelligent and personalized lower limb rehabilitation exoskeleton machines is still a significant problem. Through literature research, this paper compares and analyzes different types of lower limb rehabilitation exoskeletons in terms of their different structural forms, drive modes, and control strategies, to understand their advantages and disadvantages as well as their applicability, and puts forward an outlook on the development of lower limb rehabilitation exoskeletons in the future. Eventually, through the discussion and summary, we conclude that the future of lower limb rehabilitation exoskeleton robots will be developed in the direction of lightweight, safe, intelligent, etc., to provide rehabilitation patients with more efficient and perfect rehabilitation assistance services. © 2024 SPIE.

关键词： Exoskeleton (robotics)

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Implementation of Three-loop control for High-performance Servo Motor control using Digital Signal Processors 3

Implementation of Three-loop Control for High-performance Se...

引用

3rd international conference on control and intelligent robotics, ICCIR 2023

作者： Zhang, Huaxin Wang, Kaimeng Ju, Hehua College of Astronautics Nanjing University of Aeronautics and Astronautics Nanjing210016 China

ISBN: (纸本)9781510671867

In this paper, we present a novel method for implementing three-loop control of motors using digital signal processors (DSP). We introduce a fast current loop algorithm (FCL) to enhance the control performance of the servo motors. The three separate loops include the position, speed, and current control respectively. We implemented the three-loop control of motors using a TI C2000 series DSP and conducted laboratory testing. By comparison with traditional control methods, the proposed control method exhibits higher response speed, lower overshoot and greater resistance to external disturbances and system parameter changes. Hence, this method can be widely adopted in high-performance servo motor control applications. © 2023 SPIE.

关键词： Digital signal processors

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Microfluidic Lab-on-a-Chip Design and Analysis for GFAP Biomarker Detection Using Machine Learning Algorithms 3

Microfluidic Lab-on-a-Chip Design and Analysis for GFAP Biom...

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3rd international conference on Communication, control, and intelligent Systems, CCIS 2024

作者： Balaji, P. Devasena, D. Rithick, P. Karthi, T. Rishmitha, K. Roopa, R. Sri Ramakrishna Engineering College Dept. Of. Electronics and Instrumentation Engineering Tamilnadu Coimbatore India Sri Ramakrishna Engineering College Dept. of Robotics and Automation Engineering Tamilnadu Coimbatore India Kongu Engineering College Dept. of Automobile Engineering Erode India Science Arjun College of Technology Dept. of Artificial Intelligence and Data Tamilnadu Coimbatore India

ISBN: (纸本)9798331528201

The detection of Glial Fibrillary Acidic Protein (GFAP) is a crucial biomarker for diagnosing neurological conditions such as traumatic brain injuries (TBI) and astrocytoma. This paper presents the design and analysis of a novel microfluidic Lab-on-a-Chip (LoC) platform for GFAP biomarker detection. The system integrates microfluidic channels with embedded gold nanoparticle-functionalized electrochemical sensors for high-sensitivity biomarker capture. The microfluidic chip is designed using soft lithography and PDMS (Polydimethylsiloxane), allowing for precise fluid handling and minimal sample consumption. The electrochemical sensors generate voltage signals corresponding to GFAP concentration levels, which are processed using digital filtering techniques to mitigate noise and improve signal quality. For accurate biomarker quantification, machine learning algorithms, including Random Forest ,KNN and Support Vector Machine (SVM), are employed to classify sensor output data into clinically significant concentration ranges. The model is trained on both simulated and experimentally collected sensor data, achieving an accuracy of over 93 percent in distinguishing low (below 50 ng/mL) and high (above 50 ng/mL) GFAP concentrations. The combination of microfluidic precision, sensitive electrochemical detection, and data analysis enables rapid and reliable detection of GFAP , providing a scalable and portable solution for early diagnosis of brain injuries and neurodegenerative diseases. This system highlights the potential of integrating microfluidics and machine learning in next-generation point-of-care diagnostic devices. © 2024 IEEE.

关键词： Polydimethylsiloxane

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