Pub Date : 2022-05-26DOI: 10.1109/ICSSE55923.2022.9947361
Laura Álvarez-Hidalgo, I. Howard
The aim of the paper is to present an inverted pendulum system that operates in two different modes. Firstly, it operates in a static balancing mode, during which the controller tries to keep the pendulum balanced during which the controller tries to keep the pendulum balanced and maintain the current position of the pendulum carriage. Secondly, it also operates in a velocity control mode, so that the carriage can move at a selective velocity while simultaneously maintaining pendulum balance. In order to realize these two modes of control we implement a state feedback controller and schedule gain depending on the selected mode of operation of the system. We first describe the design and construction of the system. We then perform state space analysis, build state feedback controllers designed as linear quadratic regulators (LQR), and run tests to examine the operation of the system whilst subjecting the pendulum to impulsive disturbances. In particular, we investigate differences in control behavior in static position mode and in velocity-controlled mode. We present the experimental results and discuss their implications.
{"title":"Gain scheduling for state space control of a dual-mode inverted pendulum","authors":"Laura Álvarez-Hidalgo, I. Howard","doi":"10.1109/ICSSE55923.2022.9947361","DOIUrl":"https://doi.org/10.1109/ICSSE55923.2022.9947361","url":null,"abstract":"The aim of the paper is to present an inverted pendulum system that operates in two different modes. Firstly, it operates in a static balancing mode, during which the controller tries to keep the pendulum balanced during which the controller tries to keep the pendulum balanced and maintain the current position of the pendulum carriage. Secondly, it also operates in a velocity control mode, so that the carriage can move at a selective velocity while simultaneously maintaining pendulum balance. In order to realize these two modes of control we implement a state feedback controller and schedule gain depending on the selected mode of operation of the system. We first describe the design and construction of the system. We then perform state space analysis, build state feedback controllers designed as linear quadratic regulators (LQR), and run tests to examine the operation of the system whilst subjecting the pendulum to impulsive disturbances. In particular, we investigate differences in control behavior in static position mode and in velocity-controlled mode. We present the experimental results and discuss their implications.","PeriodicalId":220599,"journal":{"name":"2022 International Conference on System Science and Engineering (ICSSE)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127378574","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
SpO2, also known as blood oxygen saturation, is a vital physiological indicator in clinical care. Since the outbreak of COVID-19, silent hypoxia has been one of the most serious symptoms. This symptom makes the patient’s SpO2 drop to an extremely low level without discomfort and causes medical care delay for many patients. Therefore, regularly checking our SpO2 has become a very important matter. Recent work has been looking for convenient and contact-free ways to measure SpO2 with cameras. However, most previous studies were not robust enough and didn’t evaluate their algorithms on the data with a wide SpO2 range. In this paper, we proposed a novel non-contact method to measure SpO2 by using the weighted K-nearest neighbors (KNN) algorithm. Five features extracted from the RGB traces, POS, and CHROM signals were used in the KNN model. Two datasets using different ways to lower the SpO2 were constructed for evaluating the performance. The first one was collected through the breath-holding experiment, which induces more motion noise and confuses the actual blood oxygen features. The second dataset was collected at Song Syue Lodge, which locates at an elevation of 3150 meters and has lower oxygen concentration in the atmosphere making the SpO2 drop between the range of 80% to 90% without the need of holding breath. The proposed method outperforms the benchmark algorithms on the leave-one-subject-out and cross-dataset validation.
{"title":"Measurement of Blood Oxygen based on Remote-Photoplethysmography","authors":"Hsiang-Chun Lin, You-Cheng Dong, Bing-Jhang Wu, Bing-Fei Wu","doi":"10.1109/ICSSE55923.2022.9948229","DOIUrl":"https://doi.org/10.1109/ICSSE55923.2022.9948229","url":null,"abstract":"SpO2, also known as blood oxygen saturation, is a vital physiological indicator in clinical care. Since the outbreak of COVID-19, silent hypoxia has been one of the most serious symptoms. This symptom makes the patient’s SpO2 drop to an extremely low level without discomfort and causes medical care delay for many patients. Therefore, regularly checking our SpO2 has become a very important matter. Recent work has been looking for convenient and contact-free ways to measure SpO2 with cameras. However, most previous studies were not robust enough and didn’t evaluate their algorithms on the data with a wide SpO2 range. In this paper, we proposed a novel non-contact method to measure SpO2 by using the weighted K-nearest neighbors (KNN) algorithm. Five features extracted from the RGB traces, POS, and CHROM signals were used in the KNN model. Two datasets using different ways to lower the SpO2 were constructed for evaluating the performance. The first one was collected through the breath-holding experiment, which induces more motion noise and confuses the actual blood oxygen features. The second dataset was collected at Song Syue Lodge, which locates at an elevation of 3150 meters and has lower oxygen concentration in the atmosphere making the SpO2 drop between the range of 80% to 90% without the need of holding breath. The proposed method outperforms the benchmark algorithms on the leave-one-subject-out and cross-dataset validation.","PeriodicalId":220599,"journal":{"name":"2022 International Conference on System Science and Engineering (ICSSE)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130802892","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-05-26DOI: 10.1109/ICSSE55923.2022.9948240
Jen-Hsing Li
This paper is a practical paper, mainly focusing on the application of genetic algorithm in control. The controlled system is a second-order analog circuit system. This second-order analog circuit system is implemented with an operational amplifier and has the transfer function characteristics of a second-order system. Many control systems can be reduced to the model of the second-order system, so the control implementation of this second-order analog circuit system has its applications. Genetic algorithms were originally developed from some phenomena in genetic biology, including inheritance, mutation, natural selection, and hybridization. The main control law is to use PID control, and the three parameters of the controller are adjusted by the genetic algorithm. This framework has the advantage of hierarchy, because the low-level control uses PID control, so it can ensure that the system is controllable. As for high-level parameter tuning, genetic algorithm are used to ensure optimal control.
{"title":"Genetic Algorithm PID Control of Second-Order Analog Circuit System","authors":"Jen-Hsing Li","doi":"10.1109/ICSSE55923.2022.9948240","DOIUrl":"https://doi.org/10.1109/ICSSE55923.2022.9948240","url":null,"abstract":"This paper is a practical paper, mainly focusing on the application of genetic algorithm in control. The controlled system is a second-order analog circuit system. This second-order analog circuit system is implemented with an operational amplifier and has the transfer function characteristics of a second-order system. Many control systems can be reduced to the model of the second-order system, so the control implementation of this second-order analog circuit system has its applications. Genetic algorithms were originally developed from some phenomena in genetic biology, including inheritance, mutation, natural selection, and hybridization. The main control law is to use PID control, and the three parameters of the controller are adjusted by the genetic algorithm. This framework has the advantage of hierarchy, because the low-level control uses PID control, so it can ensure that the system is controllable. As for high-level parameter tuning, genetic algorithm are used to ensure optimal control.","PeriodicalId":220599,"journal":{"name":"2022 International Conference on System Science and Engineering (ICSSE)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115574387","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-05-26DOI: 10.1109/ICSSE55923.2022.9948248
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{"title":"IEEE Copyright and Consent Form","authors":"","doi":"10.1109/ICSSE55923.2022.9948248","DOIUrl":"https://doi.org/10.1109/ICSSE55923.2022.9948248","url":null,"abstract":"Presents the copyright information for the conference. May include reprint permission information.","PeriodicalId":220599,"journal":{"name":"2022 International Conference on System Science and Engineering (ICSSE)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124273377","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-05-26DOI: 10.1109/icsse55923.2022.9947356
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{"title":"ICSSE 2022 Cover Page","authors":"","doi":"10.1109/icsse55923.2022.9947356","DOIUrl":"https://doi.org/10.1109/icsse55923.2022.9947356","url":null,"abstract":"Presents the front cover, title page, or splash screen of the proceedings record.","PeriodicalId":220599,"journal":{"name":"2022 International Conference on System Science and Engineering (ICSSE)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117103578","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-05-26DOI: 10.1109/ICSSE55923.2022.9948238
Guo-wei Gao, Mei-Yung Chen
This paper focuses on a real-time fatigue detection flow. The system will be doing this all inside of python and building it up step by step to be able to detect a bunch of different poses and specifically signs of drowsiness. In order to do that we use a few key models and using media pipe holistic to be able to extract key points. This is going to allow us to extract key points from our face. The system uses tensorflow and keras and builds up a long short-term memory(LSTM) model to be able to predict the action which is being shown on the screen. We need to do is collect a bunch of data on all of our different key points, so we collect data on our face and save those as numpy arrays. The face detection method is based on a deep neural network using LSTM layers to go on ahead and predict that temporal component, which be able to predict action from a number of frames not just a single frame. Integrate using opencv and then proceed to make real-time predictions using the webcam.
{"title":"Base on Long Short-term Memory Network for Fatigue Detection","authors":"Guo-wei Gao, Mei-Yung Chen","doi":"10.1109/ICSSE55923.2022.9948238","DOIUrl":"https://doi.org/10.1109/ICSSE55923.2022.9948238","url":null,"abstract":"This paper focuses on a real-time fatigue detection flow. The system will be doing this all inside of python and building it up step by step to be able to detect a bunch of different poses and specifically signs of drowsiness. In order to do that we use a few key models and using media pipe holistic to be able to extract key points. This is going to allow us to extract key points from our face. The system uses tensorflow and keras and builds up a long short-term memory(LSTM) model to be able to predict the action which is being shown on the screen. We need to do is collect a bunch of data on all of our different key points, so we collect data on our face and save those as numpy arrays. The face detection method is based on a deep neural network using LSTM layers to go on ahead and predict that temporal component, which be able to predict action from a number of frames not just a single frame. Integrate using opencv and then proceed to make real-time predictions using the webcam.","PeriodicalId":220599,"journal":{"name":"2022 International Conference on System Science and Engineering (ICSSE)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130055190","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-05-26DOI: 10.1109/ICSSE55923.2022.9948250
W. Weng, Han-Pang Huang, Yu-Lin Zhao
With the rapid development of science and technology, in addition to the application of robots in industry, applications that provide services in daily life are also booming, such as shopping mall robots and elderly care robots. Therefore, this paper proposes to further enhance the effect of human-robot interaction based on hand gesture recognition and visual tracking, the robot system, and with the application of dual arms so that it can be used in general home or care centers.In hand gesture recognition, the hand gesture can be further known by the position of each keypoint after using OpenPose to obtain the information of the keypoints. In visual servoing, using YOLOv4 to identify the object to be tracked, and then uses hybrid model-based tracking to track the geometry of the object. In a robot cognitive system, it will get the engagement and intention of the elderly. Moreover, triggering human-robot interaction.
{"title":"The Application of Dual-arm Mobile Robot Systems in the Care of the Older Adults","authors":"W. Weng, Han-Pang Huang, Yu-Lin Zhao","doi":"10.1109/ICSSE55923.2022.9948250","DOIUrl":"https://doi.org/10.1109/ICSSE55923.2022.9948250","url":null,"abstract":"With the rapid development of science and technology, in addition to the application of robots in industry, applications that provide services in daily life are also booming, such as shopping mall robots and elderly care robots. Therefore, this paper proposes to further enhance the effect of human-robot interaction based on hand gesture recognition and visual tracking, the robot system, and with the application of dual arms so that it can be used in general home or care centers.In hand gesture recognition, the hand gesture can be further known by the position of each keypoint after using OpenPose to obtain the information of the keypoints. In visual servoing, using YOLOv4 to identify the object to be tracked, and then uses hybrid model-based tracking to track the geometry of the object. In a robot cognitive system, it will get the engagement and intention of the elderly. Moreover, triggering human-robot interaction.","PeriodicalId":220599,"journal":{"name":"2022 International Conference on System Science and Engineering (ICSSE)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130223401","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper aims to develop agricultural robots that can be applied to greenhouse crop harvesting by using a hybrid visual servo control method (HVSC). In the research, a depth camera was used to acquire the posture of the tomato in three-dimensional space, and visual servo control can be carried out for the tomato growing at different angles in practice. Different visual servo control methods are also discussed, including the Position-Based Visual Servo (PBVS), Image-Based Visual Servo (IBVS) and the proposed HVSC with the fuzzy dynamic control parameters. Characteristics of different visual servo control methods were discussed, and then applied to the actual harvesting. The results show that the hybrid visual servo control developed in this research has an average harvesting time of 9.40s/per and an average harvesting success rate of 96.25% for cherry tomato.
{"title":"Application of Hybrid Visual Servo Control in Agricultural Harvesting","authors":"Yi-Rong Li, Wei-Yuan Lian, Shao-Heng Liu, Zhiheng Huang, Chun-Ta Chen","doi":"10.1109/ICSSE55923.2022.9947362","DOIUrl":"https://doi.org/10.1109/ICSSE55923.2022.9947362","url":null,"abstract":"This paper aims to develop agricultural robots that can be applied to greenhouse crop harvesting by using a hybrid visual servo control method (HVSC). In the research, a depth camera was used to acquire the posture of the tomato in three-dimensional space, and visual servo control can be carried out for the tomato growing at different angles in practice. Different visual servo control methods are also discussed, including the Position-Based Visual Servo (PBVS), Image-Based Visual Servo (IBVS) and the proposed HVSC with the fuzzy dynamic control parameters. Characteristics of different visual servo control methods were discussed, and then applied to the actual harvesting. The results show that the hybrid visual servo control developed in this research has an average harvesting time of 9.40s/per and an average harvesting success rate of 96.25% for cherry tomato.","PeriodicalId":220599,"journal":{"name":"2022 International Conference on System Science and Engineering (ICSSE)","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133795264","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-05-26DOI: 10.1109/ICSSE55923.2022.9948257
Presents the copyright information for the conference. May include reprint permission information.
展示会议的版权信息。可能包括转载许可信息。
{"title":"IEEE Copyright and Consent Form","authors":"","doi":"10.1109/ICSSE55923.2022.9948257","DOIUrl":"https://doi.org/10.1109/ICSSE55923.2022.9948257","url":null,"abstract":"Presents the copyright information for the conference. May include reprint permission information.","PeriodicalId":220599,"journal":{"name":"2022 International Conference on System Science and Engineering (ICSSE)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125673945","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-05-26DOI: 10.1109/ICSSE55923.2022.9948251
Mengdi Wu, Bing-Gang Jhong, Mei-Yung Chen
This thesis proposes a novel controller design for a six-axes robotic arm, based on the neural network frame learning mechanism. The controller structure includes five parts. Firstly, we get the training dataset from the actual construction of the six-axis robotic arm. Secondly, the training method of the neural network is based on adaptively adjust the weight value and error between the input layer and the hidden layer. Thirdly, put the training dataset as input of the neural network to train the model. Finally, we use Lyapunov theory to guarantee the stability of the controller design for a six-axis robotic arm, and compare it with PID controller design.
{"title":"Apply Adaptive Neural Network PID Controllers for a 6DOF Robotic Arm","authors":"Mengdi Wu, Bing-Gang Jhong, Mei-Yung Chen","doi":"10.1109/ICSSE55923.2022.9948251","DOIUrl":"https://doi.org/10.1109/ICSSE55923.2022.9948251","url":null,"abstract":"This thesis proposes a novel controller design for a six-axes robotic arm, based on the neural network frame learning mechanism. The controller structure includes five parts. Firstly, we get the training dataset from the actual construction of the six-axis robotic arm. Secondly, the training method of the neural network is based on adaptively adjust the weight value and error between the input layer and the hidden layer. Thirdly, put the training dataset as input of the neural network to train the model. Finally, we use Lyapunov theory to guarantee the stability of the controller design for a six-axis robotic arm, and compare it with PID controller design.","PeriodicalId":220599,"journal":{"name":"2022 International Conference on System Science and Engineering (ICSSE)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121887449","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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