Pub Date : 2020-11-20DOI: 10.1109/ICRAE50850.2020.9310804
Jinmin Peng, Wenyu Liu, Tongfei You, Binglong Wu
Aiming at the problems of insufficient workpiece identification and detection accuracy in industrial scenes and difficulty in positioning multiple workpieces, a detection algorithm for identifying workpieces is proposed. Based on the YOLO-V3 algorithm, the network structure and multi-scale detection are improved, and the idea of hollow convolution is introduced. The residual dense block is used to replace the residual block in the original algorithm and combined with the convolutional layer to enhance the network's extraction of workpiece feature information. The original 3 scale detection is increased to 5 scale detection to improve the detection ability of small objects, Through the hollow convolution to expand the feature map of the workpiece to assist the network to extract deep-level object features, use the Kinect v2 sensor to collect the image of the workpiece and make it into a data set, the improved algorithm is tested on the data set, the experimental results show: The average detection accuracy of the workpiece reaches 92.98%, which is about 5% higher than the accuracy of the original algorithm. The combination of this method and robot grasping technology can replace manual labor to effectively complete the sorting of workpieces in industrial scenes.
{"title":"Improved YOLO-V3 Workpiece Detection Method for Sorting","authors":"Jinmin Peng, Wenyu Liu, Tongfei You, Binglong Wu","doi":"10.1109/ICRAE50850.2020.9310804","DOIUrl":"https://doi.org/10.1109/ICRAE50850.2020.9310804","url":null,"abstract":"Aiming at the problems of insufficient workpiece identification and detection accuracy in industrial scenes and difficulty in positioning multiple workpieces, a detection algorithm for identifying workpieces is proposed. Based on the YOLO-V3 algorithm, the network structure and multi-scale detection are improved, and the idea of hollow convolution is introduced. The residual dense block is used to replace the residual block in the original algorithm and combined with the convolutional layer to enhance the network's extraction of workpiece feature information. The original 3 scale detection is increased to 5 scale detection to improve the detection ability of small objects, Through the hollow convolution to expand the feature map of the workpiece to assist the network to extract deep-level object features, use the Kinect v2 sensor to collect the image of the workpiece and make it into a data set, the improved algorithm is tested on the data set, the experimental results show: The average detection accuracy of the workpiece reaches 92.98%, which is about 5% higher than the accuracy of the original algorithm. The combination of this method and robot grasping technology can replace manual labor to effectively complete the sorting of workpieces in industrial scenes.","PeriodicalId":296832,"journal":{"name":"2020 5th International Conference on Robotics and Automation Engineering (ICRAE)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127511286","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 : 2020-11-20DOI: 10.1109/ICRAE50850.2020.9310866
Siyu Wan
With the development of modern technologies, intelligent mobile robots are widely needed. However, the challenges in path planning and obstacles avoiding for mobile robots still remain. When the obstacles dynamically appear and the robot does not know the exact location of the obstacles as well as the shape of the obstacles, how to conduct efficient path finding and obstacle avoiding is still open. In this paper, we investigate how a self-walking robot can observe and adopt efficient strategies to avoid the dynamic obstacles that appear in the way to the destination. We propose a practical robot navigation model while considering the dimension of the robot and the obstacles observed. Based on this model, efficient navigation algorithms are developed using the proposed techniques of surpassing, bypassing, and virtual blocks. Our experiment and implementation with V-REP shows that the proposed schemes are effective in path planning and obstacle avoiding.
{"title":"Efficient Path Planning and Real-Time Obstacle Avoidance for Mobile Robots","authors":"Siyu Wan","doi":"10.1109/ICRAE50850.2020.9310866","DOIUrl":"https://doi.org/10.1109/ICRAE50850.2020.9310866","url":null,"abstract":"With the development of modern technologies, intelligent mobile robots are widely needed. However, the challenges in path planning and obstacles avoiding for mobile robots still remain. When the obstacles dynamically appear and the robot does not know the exact location of the obstacles as well as the shape of the obstacles, how to conduct efficient path finding and obstacle avoiding is still open. In this paper, we investigate how a self-walking robot can observe and adopt efficient strategies to avoid the dynamic obstacles that appear in the way to the destination. We propose a practical robot navigation model while considering the dimension of the robot and the obstacles observed. Based on this model, efficient navigation algorithms are developed using the proposed techniques of surpassing, bypassing, and virtual blocks. Our experiment and implementation with V-REP shows that the proposed schemes are effective in path planning and obstacle avoiding.","PeriodicalId":296832,"journal":{"name":"2020 5th International Conference on Robotics and Automation Engineering (ICRAE)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131464948","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 : 2020-11-20DOI: 10.1109/ICRAE50850.2020.9310900
Hor Tan, Latifah Nurahmi, B. Pramujati, S. Caro
This paper proposes a Cable-Driven Parallel Robot (CDPR) with three mobile cranes for search-and-rescue operations. Each mobile crane is composed of a reconfigurable telescopic boom which can be rotated. A cable is mounted from the tip of the telescopic boom to the end-effector. The locations of mobile cranes are fixed but the configuration of the telescopic boom can be adjusted to enlarge the workspace and to maintain the overall system in equilibrium. The static equilibrium of end-effector and mobile cranes is initially studied to determine the cable tension distribution and wrench-feasible-workspace. To guarantee all mobile cranes to be always in static equilibrium when executing a given task, the telescopic booms are reconfigured. Three case studies for the reconfigurable CDPR with multiple mobile cranes are presented to compare the tension distribution and workspace size.
{"title":"On the Reconfiguration of Cable-Driven Parallel Robots with Multiple Mobile Cranes","authors":"Hor Tan, Latifah Nurahmi, B. Pramujati, S. Caro","doi":"10.1109/ICRAE50850.2020.9310900","DOIUrl":"https://doi.org/10.1109/ICRAE50850.2020.9310900","url":null,"abstract":"This paper proposes a Cable-Driven Parallel Robot (CDPR) with three mobile cranes for search-and-rescue operations. Each mobile crane is composed of a reconfigurable telescopic boom which can be rotated. A cable is mounted from the tip of the telescopic boom to the end-effector. The locations of mobile cranes are fixed but the configuration of the telescopic boom can be adjusted to enlarge the workspace and to maintain the overall system in equilibrium. The static equilibrium of end-effector and mobile cranes is initially studied to determine the cable tension distribution and wrench-feasible-workspace. To guarantee all mobile cranes to be always in static equilibrium when executing a given task, the telescopic booms are reconfigured. Three case studies for the reconfigurable CDPR with multiple mobile cranes are presented to compare the tension distribution and workspace size.","PeriodicalId":296832,"journal":{"name":"2020 5th International Conference on Robotics and Automation Engineering (ICRAE)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129690686","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 : 2020-11-20DOI: 10.1109/ICRAE50850.2020.9310803
Z. Lipeng, Zhu Haifeng, Barbe David, Yang Xin, Chen Ting
AVL Company has been developing for several years autonomous driving technologies. This article describes the scope of trajectory planning and motion control algorithm and respective performances for the Automated Valet Parking (AVP) function. This function has been developed on an AVL vehicle demonstrator in Shanghai Technical Center (STC). The trajectory planner allows planning in structured environment given reference waypoints. During shuttling, typical Open Planner algorithm is applied for trajectory generation and selection. During parking maneuver, a combination of Hybrid A Star and Reeds-Shepp algorithm are used. Real time improvement of such combination is measured and compared with pure Hybrid A Star approach. Evaluation is performed both on Model in Loop (MiL) and on real vehicle. Additionally, a method to assess the real tests performance of the AVP function on AVL demonstrator vehicle using two different motion controllers is herein presented in order to provide a complete synthesis of challenges related to motion control.
{"title":"Trajectory Planner and Motion Control Solution for Automated Valet Parking Function","authors":"Z. Lipeng, Zhu Haifeng, Barbe David, Yang Xin, Chen Ting","doi":"10.1109/ICRAE50850.2020.9310803","DOIUrl":"https://doi.org/10.1109/ICRAE50850.2020.9310803","url":null,"abstract":"AVL Company has been developing for several years autonomous driving technologies. This article describes the scope of trajectory planning and motion control algorithm and respective performances for the Automated Valet Parking (AVP) function. This function has been developed on an AVL vehicle demonstrator in Shanghai Technical Center (STC). The trajectory planner allows planning in structured environment given reference waypoints. During shuttling, typical Open Planner algorithm is applied for trajectory generation and selection. During parking maneuver, a combination of Hybrid A Star and Reeds-Shepp algorithm are used. Real time improvement of such combination is measured and compared with pure Hybrid A Star approach. Evaluation is performed both on Model in Loop (MiL) and on real vehicle. Additionally, a method to assess the real tests performance of the AVP function on AVL demonstrator vehicle using two different motion controllers is herein presented in order to provide a complete synthesis of challenges related to motion control.","PeriodicalId":296832,"journal":{"name":"2020 5th International Conference on Robotics and Automation Engineering (ICRAE)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125133110","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 : 2020-11-20DOI: 10.1109/ICRAE50850.2020.9310801
Adithya K, Saurabh Jacob Kuruvila, Sarang Pramode, Niranjana Krupa
This study aims to record and translate the process of motor imagery to enable orthotic extension and flexion of the finger. This study probes the feasibility of developing a Brain Computer Interface system by prioritizing - Data Acquisition, Deep Learning, and End Effector of the system. The optimal channels to record MI data were deduced using Recursive Feature Elimination from a sixty four channel online dataset. Eight electrode channels of the OpenBCI Cyton kit were used, covering the sensorimotor cortex region of five subjects to record electroencephalographic data by following a standardized EEG acquisition protocol. Classification of tasks was carried out on a custom deep learning architecture using a convolutional layer and LSTM. The results were passed to an orthotic brace that provided a kinesthetic feedback mechanism to improve grip strength and support the neurorehabilitation of its user.
{"title":"Brain Computer Interface for Neurorehabilitation with Kinesthetic Feedback","authors":"Adithya K, Saurabh Jacob Kuruvila, Sarang Pramode, Niranjana Krupa","doi":"10.1109/ICRAE50850.2020.9310801","DOIUrl":"https://doi.org/10.1109/ICRAE50850.2020.9310801","url":null,"abstract":"This study aims to record and translate the process of motor imagery to enable orthotic extension and flexion of the finger. This study probes the feasibility of developing a Brain Computer Interface system by prioritizing - Data Acquisition, Deep Learning, and End Effector of the system. The optimal channels to record MI data were deduced using Recursive Feature Elimination from a sixty four channel online dataset. Eight electrode channels of the OpenBCI Cyton kit were used, covering the sensorimotor cortex region of five subjects to record electroencephalographic data by following a standardized EEG acquisition protocol. Classification of tasks was carried out on a custom deep learning architecture using a convolutional layer and LSTM. The results were passed to an orthotic brace that provided a kinesthetic feedback mechanism to improve grip strength and support the neurorehabilitation of its user.","PeriodicalId":296832,"journal":{"name":"2020 5th International Conference on Robotics and Automation Engineering (ICRAE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130308798","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 : 2020-11-20DOI: 10.1109/ICRAE50850.2020.9310898
J. Ziehn, M. Ruf, M. Roschani, J. Beyerer
Models for vehicle dynamics play an important role in maneuver planning for automated driving. They are used to derive trajectories from given control inputs, or to evaluate a given trajectory in terms of constraint violation or optimality criteria such as safety, comfort or ecology. Depending on the computation process, models with different assumptions and levels of detail are used; since maneuver planning usually has strong requirements for computation speed at a potentially high number of trajectory evaluations per planning cycle, most of the applied models aim to reduce complexity by implicitly or explicitly introducing simplifying assumptions. While evaluations show that these assumptions may be sufficiently valid under typical conditions, their effect has yet to be studied conclusively. We propose a model for vehicle dynamics that is convenient for maneuver planning by supporting both an analytic approach of extracting parameters from a given trajectory, and a generative approach of establishing a trajectory from given control inputs. Both applications of the model are evaluated in real-world test drives under dynamic conditions, both on a closed-off test track and on public roads, and effects arising from the simplifying assumptions are analyzed.
{"title":"Accuracy Evaluation of a Lightweight Analytic Vehicle Dynamics Model for Maneuver Planning*","authors":"J. Ziehn, M. Ruf, M. Roschani, J. Beyerer","doi":"10.1109/ICRAE50850.2020.9310898","DOIUrl":"https://doi.org/10.1109/ICRAE50850.2020.9310898","url":null,"abstract":"Models for vehicle dynamics play an important role in maneuver planning for automated driving. They are used to derive trajectories from given control inputs, or to evaluate a given trajectory in terms of constraint violation or optimality criteria such as safety, comfort or ecology. Depending on the computation process, models with different assumptions and levels of detail are used; since maneuver planning usually has strong requirements for computation speed at a potentially high number of trajectory evaluations per planning cycle, most of the applied models aim to reduce complexity by implicitly or explicitly introducing simplifying assumptions. While evaluations show that these assumptions may be sufficiently valid under typical conditions, their effect has yet to be studied conclusively. We propose a model for vehicle dynamics that is convenient for maneuver planning by supporting both an analytic approach of extracting parameters from a given trajectory, and a generative approach of establishing a trajectory from given control inputs. Both applications of the model are evaluated in real-world test drives under dynamic conditions, both on a closed-off test track and on public roads, and effects arising from the simplifying assumptions are analyzed.","PeriodicalId":296832,"journal":{"name":"2020 5th International Conference on Robotics and Automation Engineering (ICRAE)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129323473","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 : 2020-11-20DOI: 10.1109/ICRAE50850.2020.9310880
A. Liang
We first found this inverted retina structure of human and vertebrates is biological optical AI, which is consisted of optical fiber couplers and saturable absorbers. In this paper, we study the strong fiber coupling effects among seven identical human foveal cones. We first found there are biological transistors and biological diodes on retinas and brains of human and other animals. We shall discuss bionic applications of optical AI as well.
{"title":"Biological Optical AI and Bionic Optical AI","authors":"A. Liang","doi":"10.1109/ICRAE50850.2020.9310880","DOIUrl":"https://doi.org/10.1109/ICRAE50850.2020.9310880","url":null,"abstract":"We first found this inverted retina structure of human and vertebrates is biological optical AI, which is consisted of optical fiber couplers and saturable absorbers. In this paper, we study the strong fiber coupling effects among seven identical human foveal cones. We first found there are biological transistors and biological diodes on retinas and brains of human and other animals. We shall discuss bionic applications of optical AI as well.","PeriodicalId":296832,"journal":{"name":"2020 5th International Conference on Robotics and Automation Engineering (ICRAE)","volume":"102 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126245315","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 : 2020-11-20DOI: 10.1109/ICRAE50850.2020.9310867
Zhengwei Wang, Yahui Gan, X. Dai, Bo Zhou, Fang Fang
In this paper, focusing on the vision-based dual-arm collaborative assembly, a knowledge-based representation model is proposed. Different from the traditional assembly behavior in which the assembly parameters are obtained by fixing the assembly object at a specified position in a specified posture, the proposed model uses the prior knowledge bound to the model to generate assembly parameters through point cloud matching and calculation. To a certain extent, the dependence and restriction on the fixing device during the assembly process are eliminated. And the proposed is verified on ABB YuMi. The simulations prove that the proposed approach can achieve a good performance for assembly tasks.
{"title":"Combining Vision Sensing with Knowledge Database for Environmental Modeling in Dual-arm Robot Assembly Task","authors":"Zhengwei Wang, Yahui Gan, X. Dai, Bo Zhou, Fang Fang","doi":"10.1109/ICRAE50850.2020.9310867","DOIUrl":"https://doi.org/10.1109/ICRAE50850.2020.9310867","url":null,"abstract":"In this paper, focusing on the vision-based dual-arm collaborative assembly, a knowledge-based representation model is proposed. Different from the traditional assembly behavior in which the assembly parameters are obtained by fixing the assembly object at a specified position in a specified posture, the proposed model uses the prior knowledge bound to the model to generate assembly parameters through point cloud matching and calculation. To a certain extent, the dependence and restriction on the fixing device during the assembly process are eliminated. And the proposed is verified on ABB YuMi. The simulations prove that the proposed approach can achieve a good performance for assembly tasks.","PeriodicalId":296832,"journal":{"name":"2020 5th International Conference on Robotics and Automation Engineering (ICRAE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130531080","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 : 2020-11-20DOI: 10.1109/icrae50850.2020.9310889
{"title":"ICRAE 2020 Copyright Page","authors":"","doi":"10.1109/icrae50850.2020.9310889","DOIUrl":"https://doi.org/10.1109/icrae50850.2020.9310889","url":null,"abstract":"","PeriodicalId":296832,"journal":{"name":"2020 5th International Conference on Robotics and Automation Engineering (ICRAE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130024811","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 : 2020-11-20DOI: 10.1109/ICRAE50850.2020.9310827
S. Mariani, S. E. Azam
Flexible and composite structures often develop hidden damages, e.g. cracks or delamination between laminae or phases. Such events could be sensed through embedded structural health monitoring (SHM) systems, but past experimental studies in the literature proved that embedding sensors for SHM purposes may decrease the reliability of the structure, as the sensor acts as an inclusion. In former studies, the authors proposed to adopt a surface-mounted SHM approach based on inertial MEMS (micro electro-mechanical systems) sensors, which has two advantages: it is low cost and also it avoids the afore-mentioned detrimental effects on the endurance limit state of the structure. However, the low accuracy of the MEMS sensors and the type of response that they can measure may hinder an effective monitoring of the structural state; this can be overcome through redundancy and an efficient sensor placement. In this article, an automated approach is discussed for obtaining the optimal topology of a sparse MEMS sensor network. In this regard, the scenarios are assumed unknown in terms of extent and location of stiffness degradation due to damage. The optimal sensor locations are obtained via maximization of the global sensitivity of the measurements to damage. The method can be also implemented in a multi-scale framework, to efficiently handle (micro) sensors, (meso) damaged regions and (macro) structural components of (by far) different sizes. Data related to composite specimens and panels are discussed, with the aim of assessing the identifiability of damage through self-adapting theoretical/numerical (digital) twins of the monitored structures.
{"title":"Health Monitoring of Flexible Structures Via Surface-mounted Microsensors: Network Optimization and Damage Detection","authors":"S. Mariani, S. E. Azam","doi":"10.1109/ICRAE50850.2020.9310827","DOIUrl":"https://doi.org/10.1109/ICRAE50850.2020.9310827","url":null,"abstract":"Flexible and composite structures often develop hidden damages, e.g. cracks or delamination between laminae or phases. Such events could be sensed through embedded structural health monitoring (SHM) systems, but past experimental studies in the literature proved that embedding sensors for SHM purposes may decrease the reliability of the structure, as the sensor acts as an inclusion. In former studies, the authors proposed to adopt a surface-mounted SHM approach based on inertial MEMS (micro electro-mechanical systems) sensors, which has two advantages: it is low cost and also it avoids the afore-mentioned detrimental effects on the endurance limit state of the structure. However, the low accuracy of the MEMS sensors and the type of response that they can measure may hinder an effective monitoring of the structural state; this can be overcome through redundancy and an efficient sensor placement. In this article, an automated approach is discussed for obtaining the optimal topology of a sparse MEMS sensor network. In this regard, the scenarios are assumed unknown in terms of extent and location of stiffness degradation due to damage. The optimal sensor locations are obtained via maximization of the global sensitivity of the measurements to damage. The method can be also implemented in a multi-scale framework, to efficiently handle (micro) sensors, (meso) damaged regions and (macro) structural components of (by far) different sizes. Data related to composite specimens and panels are discussed, with the aim of assessing the identifiability of damage through self-adapting theoretical/numerical (digital) twins of the monitored structures.","PeriodicalId":296832,"journal":{"name":"2020 5th International Conference on Robotics and Automation Engineering (ICRAE)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132560285","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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