Pub Date : 2021-08-23DOI: 10.1109/CASE49439.2021.9551667
Gustavo B. P. Barbosa, Eduardo C. Da Silva, A. C. Leite
In this work, we present a new robust vision-based controller for wheeled mobile robots, equipped with a fixed monocular camera, to perform autonomous navigation in agricultural fields accurately. Here, we consider the existence of uncertainties in the parameters of the robot-camera system and external disturbances caused by high driving velocities, sparse plants, and terrain unevenness. Then, we design a robust image-based visual servoing (rIBVS) approach based on the sliding mode control (SMC) method for robot motion stabilization, even under the presence of such inaccuracies and perturbations. The vision-based controller, based on column and row primitives, is slightly modified to include a robustness term into the original feedback control laws to ensure successful row crop reaching and following tasks. We employ the Lyapunov stability theory to verify the stability and robustness properties of the overall closed-loop system. 3D computer simulations are carried out in the ROS-Gazebo platform, an open-source robotics simulator, using a differential-drive mobile robot (DDMR) in an ad-hoc developed row crop environment to illustrate the effectiveness and feasibility of the proposed control methodology.
{"title":"Robust Image-based Visual Servoing for Autonomous Row Crop Following with Wheeled Mobile Robots*","authors":"Gustavo B. P. Barbosa, Eduardo C. Da Silva, A. C. Leite","doi":"10.1109/CASE49439.2021.9551667","DOIUrl":"https://doi.org/10.1109/CASE49439.2021.9551667","url":null,"abstract":"In this work, we present a new robust vision-based controller for wheeled mobile robots, equipped with a fixed monocular camera, to perform autonomous navigation in agricultural fields accurately. Here, we consider the existence of uncertainties in the parameters of the robot-camera system and external disturbances caused by high driving velocities, sparse plants, and terrain unevenness. Then, we design a robust image-based visual servoing (rIBVS) approach based on the sliding mode control (SMC) method for robot motion stabilization, even under the presence of such inaccuracies and perturbations. The vision-based controller, based on column and row primitives, is slightly modified to include a robustness term into the original feedback control laws to ensure successful row crop reaching and following tasks. We employ the Lyapunov stability theory to verify the stability and robustness properties of the overall closed-loop system. 3D computer simulations are carried out in the ROS-Gazebo platform, an open-source robotics simulator, using a differential-drive mobile robot (DDMR) in an ad-hoc developed row crop environment to illustrate the effectiveness and feasibility of the proposed control methodology.","PeriodicalId":232083,"journal":{"name":"2021 IEEE 17th International Conference on Automation Science and Engineering (CASE)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114157627","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 : 2021-08-23DOI: 10.1109/CASE49439.2021.9551468
Jing Huang, Q. Chang, J. Arinez
Product completion time is a random variable resulting from the random disturbances in production systems that delay the processing of products unexpectedly. Existing methods for product completion time prediction mostly predict its mean value. However, mean value only accounts for the first moment of a probability distribution, and is not sufficient for depicting the full spread of the product completion time. In this paper, we propose a novel method for predicting the probability distribution of production completion time by combining system model and deep learning. The original data collected from the plant floor are boosted through a model-based oversampling process. The location family of Tweedie distribution is discovered to fit the distribution of product competition time well. A hybrid framework is established to predict distribution parameters given system state as input, so as to predict the completion time distributions in a real-time fashion. The location parameter is analytically evaluated with system model. Other parameters are predicted or determined with data-driven methods, including a long-short term memory network and classic Tweedie prediction techniques.
{"title":"Predicting the Distribution of Product Completion Time in Multi-Product Manufacturing Systems","authors":"Jing Huang, Q. Chang, J. Arinez","doi":"10.1109/CASE49439.2021.9551468","DOIUrl":"https://doi.org/10.1109/CASE49439.2021.9551468","url":null,"abstract":"Product completion time is a random variable resulting from the random disturbances in production systems that delay the processing of products unexpectedly. Existing methods for product completion time prediction mostly predict its mean value. However, mean value only accounts for the first moment of a probability distribution, and is not sufficient for depicting the full spread of the product completion time. In this paper, we propose a novel method for predicting the probability distribution of production completion time by combining system model and deep learning. The original data collected from the plant floor are boosted through a model-based oversampling process. The location family of Tweedie distribution is discovered to fit the distribution of product competition time well. A hybrid framework is established to predict distribution parameters given system state as input, so as to predict the completion time distributions in a real-time fashion. The location parameter is analytically evaluated with system model. Other parameters are predicted or determined with data-driven methods, including a long-short term memory network and classic Tweedie prediction techniques.","PeriodicalId":232083,"journal":{"name":"2021 IEEE 17th International Conference on Automation Science and Engineering (CASE)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124935516","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 : 2021-08-23DOI: 10.1109/CASE49439.2021.9551434
L. B. Paet, S. Santra, Mickaël Laîné, Kazuya Yoshida
This work focuses on the wireless connectivity of multi-agent lunar robotic systems and how it can be preserved during large-scale lunar exploration missions. In particular, we consider in this work the connectivity of systems composed of a single lunar module and several micro-rovers performing coordinated area coverage exploration tasks. To this end, we adopted a deterministic model for lunar radio propagation to predict the status of point-to-point communication links for agents operating on the moon. We then used this information to build a communication graph for the lunar micro-rover network. The Fiedler value, a metric derived from algebraic graph theory, was then utilized for evaluating the system's evolving network connectivity as the micro-rovers explore finite regions on the lunar surface. Simulations involving a network consisting of a single fixed lunar module and three mobile micro-rovers were performed to illustrate how the rovers' basic mobility can cause disruptions in network connectivity. Results of the simulations show that the overall connectivity of lunar multi-rover networks can be maintained by imposing constraints on the rovers' motion.
{"title":"Maintaining Connectivity in Multi-Rover Networks for Lunar Exploration Missions","authors":"L. B. Paet, S. Santra, Mickaël Laîné, Kazuya Yoshida","doi":"10.1109/CASE49439.2021.9551434","DOIUrl":"https://doi.org/10.1109/CASE49439.2021.9551434","url":null,"abstract":"This work focuses on the wireless connectivity of multi-agent lunar robotic systems and how it can be preserved during large-scale lunar exploration missions. In particular, we consider in this work the connectivity of systems composed of a single lunar module and several micro-rovers performing coordinated area coverage exploration tasks. To this end, we adopted a deterministic model for lunar radio propagation to predict the status of point-to-point communication links for agents operating on the moon. We then used this information to build a communication graph for the lunar micro-rover network. The Fiedler value, a metric derived from algebraic graph theory, was then utilized for evaluating the system's evolving network connectivity as the micro-rovers explore finite regions on the lunar surface. Simulations involving a network consisting of a single fixed lunar module and three mobile micro-rovers were performed to illustrate how the rovers' basic mobility can cause disruptions in network connectivity. Results of the simulations show that the overall connectivity of lunar multi-rover networks can be maintained by imposing constraints on the rovers' motion.","PeriodicalId":232083,"journal":{"name":"2021 IEEE 17th International Conference on Automation Science and Engineering (CASE)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114075264","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 : 2021-08-23DOI: 10.1109/CASE49439.2021.9551606
Kar Way Tan
Smart cities, are often perceived as urban areas that use technologies to manage resources, improve economy and enhance community livelihood. In this paper, we share an approach which uses multiple sources of data for evidence-based analysis of the public's views, concerns and sentiments on the topic related to mental wellness. We hope to bring forth a better understanding of the existing concerns of the citizens and available social support. Our study leverages on social sensing via text mining and social network analysis to listen to the voices of the citizens through revealed content from web data sources, such as social media and public forums. By using hybrid data sources, we present the important considerations for mining inherent mental wellness concerns faced by the citizens. The outcome of the analysis includes, both the positive and negative sentiments towards mental wellness and draws relations to national level performance indicators relating to mental wellness. We hope our research could help authorities derive actionable plans for designing health services or public events that bring positive social mixing and happiness by addressing the mental wellness of the residents.
{"title":"Discovery of Mental Wellness via Social Analytics for Liveability in an Urban City","authors":"Kar Way Tan","doi":"10.1109/CASE49439.2021.9551606","DOIUrl":"https://doi.org/10.1109/CASE49439.2021.9551606","url":null,"abstract":"Smart cities, are often perceived as urban areas that use technologies to manage resources, improve economy and enhance community livelihood. In this paper, we share an approach which uses multiple sources of data for evidence-based analysis of the public's views, concerns and sentiments on the topic related to mental wellness. We hope to bring forth a better understanding of the existing concerns of the citizens and available social support. Our study leverages on social sensing via text mining and social network analysis to listen to the voices of the citizens through revealed content from web data sources, such as social media and public forums. By using hybrid data sources, we present the important considerations for mining inherent mental wellness concerns faced by the citizens. The outcome of the analysis includes, both the positive and negative sentiments towards mental wellness and draws relations to national level performance indicators relating to mental wellness. We hope our research could help authorities derive actionable plans for designing health services or public events that bring positive social mixing and happiness by addressing the mental wellness of the residents.","PeriodicalId":232083,"journal":{"name":"2021 IEEE 17th International Conference on Automation Science and Engineering (CASE)","volume":"156 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122781045","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 : 2021-08-23DOI: 10.1109/CASE49439.2021.9551465
O. Omisore, Wenjing Du, Wenke Duan, Thanh-Nhon Do, Rita Orji, Lei Wang
Recent insights from human-robot intelligence and deep learning raise hope towards task-specific autonomy in robotic intravascular coronary interventions. However, lack of learning-based methods for characterizing the interventionists' kinesthetic data hinders the drive for shared control and robotic autonomy during cyborg catheterization. In this study, a deep multimodal network model is proposed for classification and recognition of interventionists' hand movements during cyborg intravascular catheterization. The model has two modules for extracting salient features in electromyography signal datasets, and classification of hand motions made during intravascular catheterization procedures. Network training and evaluation observed for in-vitro and in-vivo datasets obtained from trained novice subjects and expert with about 5 years of experience in percutaneous coronary interventions. Performance evaluation shows the learning model could classify interventionists' hand movements accurately in manual and robot-assisted navigations, respectively. This study is suggested to further stimulate the development of appropriate skill level assessments towards cyborg catheterization for cardiac interventions.
{"title":"A Deep Multimodal Network for Classification and Identification of Interventionists' Hand Motions during Cyborg Intravascular Catheterization","authors":"O. Omisore, Wenjing Du, Wenke Duan, Thanh-Nhon Do, Rita Orji, Lei Wang","doi":"10.1109/CASE49439.2021.9551465","DOIUrl":"https://doi.org/10.1109/CASE49439.2021.9551465","url":null,"abstract":"Recent insights from human-robot intelligence and deep learning raise hope towards task-specific autonomy in robotic intravascular coronary interventions. However, lack of learning-based methods for characterizing the interventionists' kinesthetic data hinders the drive for shared control and robotic autonomy during cyborg catheterization. In this study, a deep multimodal network model is proposed for classification and recognition of interventionists' hand movements during cyborg intravascular catheterization. The model has two modules for extracting salient features in electromyography signal datasets, and classification of hand motions made during intravascular catheterization procedures. Network training and evaluation observed for in-vitro and in-vivo datasets obtained from trained novice subjects and expert with about 5 years of experience in percutaneous coronary interventions. Performance evaluation shows the learning model could classify interventionists' hand movements accurately in manual and robot-assisted navigations, respectively. This study is suggested to further stimulate the development of appropriate skill level assessments towards cyborg catheterization for cardiac interventions.","PeriodicalId":232083,"journal":{"name":"2021 IEEE 17th International Conference on Automation Science and Engineering (CASE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129226706","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 : 2021-08-23DOI: 10.1109/CASE49439.2021.9551593
S. Thuijsman, M. Reniers, Dennis Hendriks
Given a model of an uncontrolled system and a requirement specification, a supervisory controller can be synthesized so that the system under control adheres to the requirements. There are several ways in which informal behavioral safety requirements can be formalized, one of which is using mutual state exclusion requirements. In current implementations of the supervisor synthesis algorithm, synthesis may be inefficient when mutual state exclusion requirements are used. We propose a method to efficiently enforce these requirements in supervisor synthesis. We consider symbolic supervisor synthesis, where Binary Decision Diagrams are used to represent the system. The efficiency of the proposed method is evaluated by means of an industrial and academic case study.
{"title":"Efficiently enforcing mutual state exclusion requirements in symbolic supervisor synthesis","authors":"S. Thuijsman, M. Reniers, Dennis Hendriks","doi":"10.1109/CASE49439.2021.9551593","DOIUrl":"https://doi.org/10.1109/CASE49439.2021.9551593","url":null,"abstract":"Given a model of an uncontrolled system and a requirement specification, a supervisory controller can be synthesized so that the system under control adheres to the requirements. There are several ways in which informal behavioral safety requirements can be formalized, one of which is using mutual state exclusion requirements. In current implementations of the supervisor synthesis algorithm, synthesis may be inefficient when mutual state exclusion requirements are used. We propose a method to efficiently enforce these requirements in supervisor synthesis. We consider symbolic supervisor synthesis, where Binary Decision Diagrams are used to represent the system. The efficiency of the proposed method is evaluated by means of an industrial and academic case study.","PeriodicalId":232083,"journal":{"name":"2021 IEEE 17th International Conference on Automation Science and Engineering (CASE)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124802753","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 : 2021-08-23DOI: 10.1109/CASE49439.2021.9551453
Orhan Özgüner, Thomas Shkurti, Su Lu, W. Newman, M. C. Cavusoglu
This paper presents a visually-guided autonomous needle driving algorithm for autonomous robotic surgical suturing. Surgical needle tracking, needle path planning, and optimum needle grasp selection algorithms are employed. The procedure is performed in 5 major steps: needle grasp, needle hand-off, needle drive, needle regrasp, and needle pull. The performance of the procedure is experimentally evaluated using the physical da Vinci® surgical robotic system and da Vinci Research Kit (dVRK). Initial results suggest that the dVRK can successfully perform needle driving with visual guidance.
本文提出了一种用于自主手术缝合机器人的视觉引导自动针驱动算法。采用手术针跟踪、针路径规划和最佳抓针选择算法。该过程分为5个主要步骤:抓针、换针、驱动、再抓针和拔针。使用物理da Vinci®手术机器人系统和da Vinci Research Kit (dVRK)对该程序的性能进行实验评估。初步结果表明，dVRK可以在视觉引导下成功进行针入。
{"title":"Visually Guided Needle Driving and Pull for Autonomous Suturing","authors":"Orhan Özgüner, Thomas Shkurti, Su Lu, W. Newman, M. C. Cavusoglu","doi":"10.1109/CASE49439.2021.9551453","DOIUrl":"https://doi.org/10.1109/CASE49439.2021.9551453","url":null,"abstract":"This paper presents a visually-guided autonomous needle driving algorithm for autonomous robotic surgical suturing. Surgical needle tracking, needle path planning, and optimum needle grasp selection algorithms are employed. The procedure is performed in 5 major steps: needle grasp, needle hand-off, needle drive, needle regrasp, and needle pull. The performance of the procedure is experimentally evaluated using the physical da Vinci® surgical robotic system and da Vinci Research Kit (dVRK). Initial results suggest that the dVRK can successfully perform needle driving with visual guidance.","PeriodicalId":232083,"journal":{"name":"2021 IEEE 17th International Conference on Automation Science and Engineering (CASE)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124971535","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 : 2021-08-23DOI: 10.1109/CASE49439.2021.9551441
S. Sajjadi, M. M. H. Fallah, M. Mehrandezh, F. Janabi-Sharifi
Image-based visual predictive controllers have gained attention due to their optimality and constraint-handling capabilities. However, their performance deteriorates in presence of the modelling and measurement uncertainties. This paper presents a stochastic image-based visual predictive control method to overcome some shortcomings of the previous schemes cited in literature. In particular, the proposed approach provides a systematic solution to address the image-based constraint compliance in presence of the measurement and modelling uncertainties. The proposed method was implemented on a 6-DOF Denso robot via simulation.
{"title":"Stochastic Image-based Visual Predictive Control","authors":"S. Sajjadi, M. M. H. Fallah, M. Mehrandezh, F. Janabi-Sharifi","doi":"10.1109/CASE49439.2021.9551441","DOIUrl":"https://doi.org/10.1109/CASE49439.2021.9551441","url":null,"abstract":"Image-based visual predictive controllers have gained attention due to their optimality and constraint-handling capabilities. However, their performance deteriorates in presence of the modelling and measurement uncertainties. This paper presents a stochastic image-based visual predictive control method to overcome some shortcomings of the previous schemes cited in literature. In particular, the proposed approach provides a systematic solution to address the image-based constraint compliance in presence of the measurement and modelling uncertainties. The proposed method was implemented on a 6-DOF Denso robot via simulation.","PeriodicalId":232083,"journal":{"name":"2021 IEEE 17th International Conference on Automation Science and Engineering (CASE)","volume":"151 8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131124291","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 : 2021-08-23DOI: 10.1109/CASE49439.2021.9551427
Yu-Cheng Hsu, Ming C. Lin, C. G. Li
Dynamically self-balancing wheeled robots possess the characteristics of having a small footprint, low base-to-height ratios, high accelerations and speeds, and low costs. They are suitable for working in human-centric environments. As part of our ongoing effort in creating self-balancing wheeled robots, in this article, we reported the development of our latest model – $mathrm{J}4.beta$. In contrast to the previous model – $mathrm{J}4.alpha$, the new model has a greater dynamic mass-to-total ratio; thus, the acceleration and the ultimate speed are both increased. Here, the maximum speed of 4.4 m/s of the motion platform is achievable by $mathrm{J}4.beta$. We analyzed the system dynamics and had confirmations from measurements; a speed servo system was developed based on PID control. To simplify the dynamics of the mobile robot, a stepper motor instead of a DC motor was adopted for the actuation of the dynamic mass; the overall controlled plant could be approximated as a second-order system. To acquire the PID coefficients, a series of road tests were performed in a common office building. A set of suitable PID coefficients was obtained and verified by three speeds: 0.5 m/s, 1 m/s, and 2 m/s. The speed curves exhibited fast ramp-up, low overshoot, setpoint matching, and low oscillation. For regulation testing, a zero speed was set and external disturbance was applied. The robot was witnessed to slow down rapidly and remain stationary without intensive oscillation. While constructing the autonomous navigation and remote control systems for the mobile robot, the sampling rate of the control system was largely upgraded to 4k Hz to achieve a better tracking and regulation ability.
{"title":"Mobility Improvement on the Two-Wheeled Dynamically Balanced Robot – $mathrm{J}4.beta$","authors":"Yu-Cheng Hsu, Ming C. Lin, C. G. Li","doi":"10.1109/CASE49439.2021.9551427","DOIUrl":"https://doi.org/10.1109/CASE49439.2021.9551427","url":null,"abstract":"Dynamically self-balancing wheeled robots possess the characteristics of having a small footprint, low base-to-height ratios, high accelerations and speeds, and low costs. They are suitable for working in human-centric environments. As part of our ongoing effort in creating self-balancing wheeled robots, in this article, we reported the development of our latest model – $mathrm{J}4.beta$. In contrast to the previous model – $mathrm{J}4.alpha$, the new model has a greater dynamic mass-to-total ratio; thus, the acceleration and the ultimate speed are both increased. Here, the maximum speed of 4.4 m/s of the motion platform is achievable by $mathrm{J}4.beta$. We analyzed the system dynamics and had confirmations from measurements; a speed servo system was developed based on PID control. To simplify the dynamics of the mobile robot, a stepper motor instead of a DC motor was adopted for the actuation of the dynamic mass; the overall controlled plant could be approximated as a second-order system. To acquire the PID coefficients, a series of road tests were performed in a common office building. A set of suitable PID coefficients was obtained and verified by three speeds: 0.5 m/s, 1 m/s, and 2 m/s. The speed curves exhibited fast ramp-up, low overshoot, setpoint matching, and low oscillation. For regulation testing, a zero speed was set and external disturbance was applied. The robot was witnessed to slow down rapidly and remain stationary without intensive oscillation. While constructing the autonomous navigation and remote control systems for the mobile robot, the sampling rate of the control system was largely upgraded to 4k Hz to achieve a better tracking and regulation ability.","PeriodicalId":232083,"journal":{"name":"2021 IEEE 17th International Conference on Automation Science and Engineering (CASE)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131364703","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 : 2021-08-23DOI: 10.1109/CASE49439.2021.9551464
Francisco J. Huertos, Beatriz Chicote, Manuel Masenlle, Mikel Ayuso
The Hyperconnected Architecture for High Cognitive Production Plants (HyperCOG) project aims at the process industry's complete digital transformation through an advanced Industrial Cyber-Physical Infrastructure. It is based on advanced technologies that allow a hyperconnected network of digital nodes to be created improving the classic automation hierarchy of communication layers. The nodes will collect data streams in real-time, offering cognitive sensing and information along with high performance computing capabilities making the process industry businesses solid in different scenarios. The system is validated in three fields of the process industry: steel, cement and chemical where optimization in the use of energy and raw materials is obtained, among other benefits.
{"title":"A Novel Architecture for Cyber-Physical Production Systems in Industry 4.0","authors":"Francisco J. Huertos, Beatriz Chicote, Manuel Masenlle, Mikel Ayuso","doi":"10.1109/CASE49439.2021.9551464","DOIUrl":"https://doi.org/10.1109/CASE49439.2021.9551464","url":null,"abstract":"The Hyperconnected Architecture for High Cognitive Production Plants (HyperCOG) project aims at the process industry's complete digital transformation through an advanced Industrial Cyber-Physical Infrastructure. It is based on advanced technologies that allow a hyperconnected network of digital nodes to be created improving the classic automation hierarchy of communication layers. The nodes will collect data streams in real-time, offering cognitive sensing and information along with high performance computing capabilities making the process industry businesses solid in different scenarios. The system is validated in three fields of the process industry: steel, cement and chemical where optimization in the use of energy and raw materials is obtained, among other benefits.","PeriodicalId":232083,"journal":{"name":"2021 IEEE 17th International Conference on Automation Science and Engineering (CASE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128725362","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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