Pub Date : 2021-10-12DOI: 10.23919/ICCAS52745.2021.9649923
Yong-Geon Kim, Min-Woo Na, Jae-Bok Song
When performing robotic assembly, a task should be conducted through force-based control such as impedance control. Using impedance control, it is possible to control the contact force by appropriately adjusting the impedance parameters. However, the impedance parameters should be set by the user because it is difficult to accurately recognize the dynamics of the contact environment, which takes a lot of time because it should be performed whenever the assembly task changes. Moreover, the parameters may not be optimal because it depends on the experience and skill level of the user. To this end, a reinforcement learning-based impedance parameter tuning method is proposed in this study. Since this method uses only the physics-based robotic simulation on the virtual environment, there is no risk of damaging the robots or parts and learning time can be significantly reduced. The proposed method was verified by assembling an HDMI connector with a tolerance of 0.03 mm. Impedance parameters were learned in the virtual environment and transferred to the real environment. Finally, it was confirmed that parameter tuning for impedance without the aid of the user is possible by using the proposed method.
{"title":"Reinforcement Learning-based Sim-to-Real Impedance Parameter Tuning for Robotic Assembly","authors":"Yong-Geon Kim, Min-Woo Na, Jae-Bok Song","doi":"10.23919/ICCAS52745.2021.9649923","DOIUrl":"https://doi.org/10.23919/ICCAS52745.2021.9649923","url":null,"abstract":"When performing robotic assembly, a task should be conducted through force-based control such as impedance control. Using impedance control, it is possible to control the contact force by appropriately adjusting the impedance parameters. However, the impedance parameters should be set by the user because it is difficult to accurately recognize the dynamics of the contact environment, which takes a lot of time because it should be performed whenever the assembly task changes. Moreover, the parameters may not be optimal because it depends on the experience and skill level of the user. To this end, a reinforcement learning-based impedance parameter tuning method is proposed in this study. Since this method uses only the physics-based robotic simulation on the virtual environment, there is no risk of damaging the robots or parts and learning time can be significantly reduced. The proposed method was verified by assembling an HDMI connector with a tolerance of 0.03 mm. Impedance parameters were learned in the virtual environment and transferred to the real environment. Finally, it was confirmed that parameter tuning for impedance without the aid of the user is possible by using the proposed method.","PeriodicalId":411064,"journal":{"name":"2021 21st International Conference on Control, Automation and Systems (ICCAS)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131766765","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 : 2021-10-12DOI: 10.23919/ICCAS52745.2021.9649822
Eunho Lee, Youngbae Hwang
Many methods have been proposed to address the real noise, they suffer from restoring the edge regions appropriately. Because most convolutional neural network-based denoising methods capture noise characteristics through pixel loss that only detects contaminated pixels, high frequency components cannot be considered. This causes blurs and artifacts on edge regions which has the high frequency component. In this paper, we apply an edge loss function to the dual adversarial network to deal with this issue. Using the edge loss and the pixel loss together, the network has been improved to restore not only the actual intensity but also the edges effectively.
{"title":"Enhanced Dual Adversarial Network for Real Image Noise Removal and Generation using Edge Loss Function","authors":"Eunho Lee, Youngbae Hwang","doi":"10.23919/ICCAS52745.2021.9649822","DOIUrl":"https://doi.org/10.23919/ICCAS52745.2021.9649822","url":null,"abstract":"Many methods have been proposed to address the real noise, they suffer from restoring the edge regions appropriately. Because most convolutional neural network-based denoising methods capture noise characteristics through pixel loss that only detects contaminated pixels, high frequency components cannot be considered. This causes blurs and artifacts on edge regions which has the high frequency component. In this paper, we apply an edge loss function to the dual adversarial network to deal with this issue. Using the edge loss and the pixel loss together, the network has been improved to restore not only the actual intensity but also the edges effectively.","PeriodicalId":411064,"journal":{"name":"2021 21st International Conference on Control, Automation and Systems (ICCAS)","volume":" 10","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132123710","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 : 2021-10-12DOI: 10.23919/ICCAS52745.2021.9649839
Kanghoon Lee, Kyuree Ahn, Jinkyoo Park
The Unmanned Surface Vehicles (USVs), which operate without a person at the surface, are used in various naval defense missions. Various missions can be conducted efficiently when a swarm of USVs are operated at the same time. However, it is challenging to establish a decentralised control strategy for all USVs. In addition, the strategy must consider various external factors, such as the ocean topography and the number of enemy forces. These difficulties necessitate a scalable and transferable decision-making module. This study proposes an algorithm to derive the decentralised and cooperative control strategy for the USV swarm using graph centric multi-agent reinforcement learning (MARL). The model first expresses the mission situation using a graph considering the various sensor ranges. Each USV agent encodes observed information into localized embedding and then derives coordinated action through communication with the surrounding agent. To derive a cooperative policy, we trained each agent's policy to maximize the team reward. Using the modified prey-predator environment of OpenAI gym, we have analyzed the effect of each component of the proposed model (state embedding, communication, and team reward). The ablation study shows that the proposed model could derive a scalable and transferable control policy of USVs, consistently achieving the highest win ratio.
{"title":"End-to-End control of USV swarm using graph centric Multi-Agent Reinforcement Learning","authors":"Kanghoon Lee, Kyuree Ahn, Jinkyoo Park","doi":"10.23919/ICCAS52745.2021.9649839","DOIUrl":"https://doi.org/10.23919/ICCAS52745.2021.9649839","url":null,"abstract":"The Unmanned Surface Vehicles (USVs), which operate without a person at the surface, are used in various naval defense missions. Various missions can be conducted efficiently when a swarm of USVs are operated at the same time. However, it is challenging to establish a decentralised control strategy for all USVs. In addition, the strategy must consider various external factors, such as the ocean topography and the number of enemy forces. These difficulties necessitate a scalable and transferable decision-making module. This study proposes an algorithm to derive the decentralised and cooperative control strategy for the USV swarm using graph centric multi-agent reinforcement learning (MARL). The model first expresses the mission situation using a graph considering the various sensor ranges. Each USV agent encodes observed information into localized embedding and then derives coordinated action through communication with the surrounding agent. To derive a cooperative policy, we trained each agent's policy to maximize the team reward. Using the modified prey-predator environment of OpenAI gym, we have analyzed the effect of each component of the proposed model (state embedding, communication, and team reward). The ablation study shows that the proposed model could derive a scalable and transferable control policy of USVs, consistently achieving the highest win ratio.","PeriodicalId":411064,"journal":{"name":"2021 21st International Conference on Control, Automation and Systems (ICCAS)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134356226","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 : 2021-10-12DOI: 10.23919/ICCAS52745.2021.9649922
Ki-Wook Jung, Chang-Hun Lee, Jun-Seong Lee, Sunghyuck Im, Keejoo Lee, Marco Sagliano, David Seelbinder
This paper aims to propose a new guidance algorithm for a rocket with aerodynamics control for launch operations, based on the concept of the instantaneous impact point (IIP). In this study, the rocket with aerodynamics control is considered with the purpose of reducing dispersion of the impact point after separation of the rocket for safety reasons. Since a very limited aerodynamic maneuverability is typically allowed for the rocket due to the structural limit, a guidance algorithm producing a huge acceleration demand is not desirable. Based on this aspect, the proposed guidance algorithm is derived directly from the underlying principle of the guidance process: forming the collision geometry towards a target point. To be more specific, the collision-ballistic-trajectory where the instantaneous impact point becomes the target point, and the corresponding heading error are first determined using a rapid ballistic trajectory prediction technique. Here, the trajectory prediction method is based on the partial closed-form solutions of the ballistic trajectory equations considering aerodynamic drag and gravity. And then, the proposed guidance algorithm works to nullify the heading error in a finite time, governed by the optimal error dynamics. The key feature of the proposed guidance algorithm lies in its simple implementation and exact collision geometry nature. Hence, the proposed method allows achieving the collision course with minimal guidance command, and it is a desirable property for the guidance algorithm of the rocket with the aerodynamics control. Finally, numerical simulations are conducted to demonstrate the effectiveness of the proposed guidance algorithms.
{"title":"An Instantaneous Impact Point Guidance for Rocket with Aerodynamics Control","authors":"Ki-Wook Jung, Chang-Hun Lee, Jun-Seong Lee, Sunghyuck Im, Keejoo Lee, Marco Sagliano, David Seelbinder","doi":"10.23919/ICCAS52745.2021.9649922","DOIUrl":"https://doi.org/10.23919/ICCAS52745.2021.9649922","url":null,"abstract":"This paper aims to propose a new guidance algorithm for a rocket with aerodynamics control for launch operations, based on the concept of the instantaneous impact point (IIP). In this study, the rocket with aerodynamics control is considered with the purpose of reducing dispersion of the impact point after separation of the rocket for safety reasons. Since a very limited aerodynamic maneuverability is typically allowed for the rocket due to the structural limit, a guidance algorithm producing a huge acceleration demand is not desirable. Based on this aspect, the proposed guidance algorithm is derived directly from the underlying principle of the guidance process: forming the collision geometry towards a target point. To be more specific, the collision-ballistic-trajectory where the instantaneous impact point becomes the target point, and the corresponding heading error are first determined using a rapid ballistic trajectory prediction technique. Here, the trajectory prediction method is based on the partial closed-form solutions of the ballistic trajectory equations considering aerodynamic drag and gravity. And then, the proposed guidance algorithm works to nullify the heading error in a finite time, governed by the optimal error dynamics. The key feature of the proposed guidance algorithm lies in its simple implementation and exact collision geometry nature. Hence, the proposed method allows achieving the collision course with minimal guidance command, and it is a desirable property for the guidance algorithm of the rocket with the aerodynamics control. Finally, numerical simulations are conducted to demonstrate the effectiveness of the proposed guidance algorithms.","PeriodicalId":411064,"journal":{"name":"2021 21st International Conference on Control, Automation and Systems (ICCAS)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134444185","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 : 2021-10-12DOI: 10.23919/ICCAS52745.2021.9649977
A. Arabí, H. Osman
The exhaust valve is responsible for the engine's smooth operation. Exhaust gases are directed from the combustion chamber to the exhaust manifold via the exhaust valve. Valve springs are subjected to tensile strains as a result of gas pressure fluctuations, fluctuating loads, and elasticity loosening as the IC engine runs. Excessive valve noise and internal engine damage can be caused by weak or cracked exhaust valve springs in an IC engine. Recent Metaheuristic Algorithms, such as Sin-Cos, PSO, GPSO, Cukoo, and ABC, are utilized in this study to find the best design parameters for the exhaust valve spring while keeping the spring's deflection, shear stresses, and fatigue in mind. The PSO and Sin-Cos algorithms outperform the others in terms of speed of convergence, while the GPSO achieves a helical spring weight of 2.1N.
{"title":"Optimal Design Parameters of Exhaust Valve Spring in IC Engines Using Metaheuristic Algorithms","authors":"A. Arabí, H. Osman","doi":"10.23919/ICCAS52745.2021.9649977","DOIUrl":"https://doi.org/10.23919/ICCAS52745.2021.9649977","url":null,"abstract":"The exhaust valve is responsible for the engine's smooth operation. Exhaust gases are directed from the combustion chamber to the exhaust manifold via the exhaust valve. Valve springs are subjected to tensile strains as a result of gas pressure fluctuations, fluctuating loads, and elasticity loosening as the IC engine runs. Excessive valve noise and internal engine damage can be caused by weak or cracked exhaust valve springs in an IC engine. Recent Metaheuristic Algorithms, such as Sin-Cos, PSO, GPSO, Cukoo, and ABC, are utilized in this study to find the best design parameters for the exhaust valve spring while keeping the spring's deflection, shear stresses, and fatigue in mind. The PSO and Sin-Cos algorithms outperform the others in terms of speed of convergence, while the GPSO achieves a helical spring weight of 2.1N.","PeriodicalId":411064,"journal":{"name":"2021 21st International Conference on Control, Automation and Systems (ICCAS)","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125608012","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 : 2021-10-12DOI: 10.23919/ICCAS52745.2021.9650060
Wen Du, Yusheng Wei, Mingjun Du
In this paper, we consider the distributed optimization problem under structurally balanced signed graph. First, we convert the original distributed optimization problem into a conditional minimum problem under the condition that the graph is structurally balanced. Our goal is to find the saddle points of augmented Lagrange function. Inspired by the Lagrange multiplier method, we present our algorithms for both undirected graph and digraph, and show that our algorithms asymptotically converge to the global minimizer. Particularly, our algorithms for digraph can not only handle the weight balanced case but the weight unbalanced case. We show that the unsigned graph is a special case of our signed graph cases. Finally, theoretical results are illustrated by numerical simulations.
{"title":"Distributed Optimization Algorithms on Structurally Balanced Signed Networks","authors":"Wen Du, Yusheng Wei, Mingjun Du","doi":"10.23919/ICCAS52745.2021.9650060","DOIUrl":"https://doi.org/10.23919/ICCAS52745.2021.9650060","url":null,"abstract":"In this paper, we consider the distributed optimization problem under structurally balanced signed graph. First, we convert the original distributed optimization problem into a conditional minimum problem under the condition that the graph is structurally balanced. Our goal is to find the saddle points of augmented Lagrange function. Inspired by the Lagrange multiplier method, we present our algorithms for both undirected graph and digraph, and show that our algorithms asymptotically converge to the global minimizer. Particularly, our algorithms for digraph can not only handle the weight balanced case but the weight unbalanced case. We show that the unsigned graph is a special case of our signed graph cases. Finally, theoretical results are illustrated by numerical simulations.","PeriodicalId":411064,"journal":{"name":"2021 21st International Conference on Control, Automation and Systems (ICCAS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129193916","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 : 2021-10-12DOI: 10.23919/ICCAS52745.2021.9650057
Jongchan Kim, In-Deok Park, Sungho Kim
Recently, research related to Advanced Driver Assistance Systems is active. In this paper, EfficientDet Fusion Framework for multi-spectral pedestrian detection is constructed through Sum, Max, and Concatenation at the feature level. In the experiment, it was confirmed that the performance improvement of the convergence multispectral network was quantitatively improved by about 10% compared to the single spectral network. In addition, it shows that the shortcomings of a single spectral can be actually compensated through the resulting image. In the future, various fusion studies will be conducted based on the EfficientDet Fusion Framework.
{"title":"A Fusion Framework for Multi-Spectral Pedestrian Detection using EfficientDet","authors":"Jongchan Kim, In-Deok Park, Sungho Kim","doi":"10.23919/ICCAS52745.2021.9650057","DOIUrl":"https://doi.org/10.23919/ICCAS52745.2021.9650057","url":null,"abstract":"Recently, research related to Advanced Driver Assistance Systems is active. In this paper, EfficientDet Fusion Framework for multi-spectral pedestrian detection is constructed through Sum, Max, and Concatenation at the feature level. In the experiment, it was confirmed that the performance improvement of the convergence multispectral network was quantitatively improved by about 10% compared to the single spectral network. In addition, it shows that the shortcomings of a single spectral can be actually compensated through the resulting image. In the future, various fusion studies will be conducted based on the EfficientDet Fusion Framework.","PeriodicalId":411064,"journal":{"name":"2021 21st International Conference on Control, Automation and Systems (ICCAS)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132189451","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 : 2021-10-12DOI: 10.23919/ICCAS52745.2021.9649770
Jee-Soo Ha, Soo-Ri Im, W. Lee, Dong-Hoon Kim, Jaekwan Ryu
This paper proposes a dynamic obstacle detection system for USV based on marine radar and Electronic Navigational chart (ENC), the most common navigation sensors on ships. This system has the advantage of enabling simple obstacle recognition without the need to additionally mount expensive equipment. In this system, we generated two types of grid maps: one is plan position indicator (PPI) images from marine radar, the other is a hull information-based grid map extracted from ENC. By accumulating the two grid map images, obstacles that appear repeatedly are classified as fixed obstacles, and obstacles that move as the grid map is updated are classified as dynamic obstacles. The proposed obstacle detection system was installed in the Sea Sword USV developed by LIGNex1 and tested in a marine environment. The system proposed in the experiment recognized the small rubber boat as a dynamic obstacle and the surrounding environment as a static obstacle. Along with our proposed obstacle detection system, it is possible to recognize obstacles through ENC and radar, which are essential equipment for ships, without video equipment.
{"title":"Radar based Obstacle Detection System for Autonomous Unmanned Surface Vehicles","authors":"Jee-Soo Ha, Soo-Ri Im, W. Lee, Dong-Hoon Kim, Jaekwan Ryu","doi":"10.23919/ICCAS52745.2021.9649770","DOIUrl":"https://doi.org/10.23919/ICCAS52745.2021.9649770","url":null,"abstract":"This paper proposes a dynamic obstacle detection system for USV based on marine radar and Electronic Navigational chart (ENC), the most common navigation sensors on ships. This system has the advantage of enabling simple obstacle recognition without the need to additionally mount expensive equipment. In this system, we generated two types of grid maps: one is plan position indicator (PPI) images from marine radar, the other is a hull information-based grid map extracted from ENC. By accumulating the two grid map images, obstacles that appear repeatedly are classified as fixed obstacles, and obstacles that move as the grid map is updated are classified as dynamic obstacles. The proposed obstacle detection system was installed in the Sea Sword USV developed by LIGNex1 and tested in a marine environment. The system proposed in the experiment recognized the small rubber boat as a dynamic obstacle and the surrounding environment as a static obstacle. Along with our proposed obstacle detection system, it is possible to recognize obstacles through ENC and radar, which are essential equipment for ships, without video equipment.","PeriodicalId":411064,"journal":{"name":"2021 21st International Conference on Control, Automation and Systems (ICCAS)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131703759","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 : 2021-10-12DOI: 10.23919/ICCAS52745.2021.9649797
Nozomi Shime, Tohru Kamiya, T. Ishida
One of the difficulties of cancer is the metastasis of cancer through the lymph nodes. Therefore, early detection and treatment of cancerous is important. Visual screening is one of useful tool for diagnosing of the cancer. However, the number of images obtained at a time is large, and the burden on the reading physician is increasing. Furthermore, reading of image is based on the subjective judgment of the physician, which may lead to different diagnostic results. To solve these problems, computer aided diagnosis (CAD) systems have been attracting attention in recent years. One of the CAD systems is the temporal subtraction image technology. In this paper, we propose an image alignment method for generating temporal subtraction images from images taken before and after contrast agent was administered to the cervical lymph nodes of the same subject. In addition, we propose an image analysis method that suppresses overextraction of lymph node candidate regions on the temporal subtraction image based on the features of lymph nodes. We applied the proposed method to the CT images of three sets and compared the temporal subtraction images with the final lymph node extraction images, and confirmed that the proposed method can suppress the overextraction of lymph node regions.
{"title":"Extraction of Cervical Lymph Nodes Based on Three-Dimensional Image Registration","authors":"Nozomi Shime, Tohru Kamiya, T. Ishida","doi":"10.23919/ICCAS52745.2021.9649797","DOIUrl":"https://doi.org/10.23919/ICCAS52745.2021.9649797","url":null,"abstract":"One of the difficulties of cancer is the metastasis of cancer through the lymph nodes. Therefore, early detection and treatment of cancerous is important. Visual screening is one of useful tool for diagnosing of the cancer. However, the number of images obtained at a time is large, and the burden on the reading physician is increasing. Furthermore, reading of image is based on the subjective judgment of the physician, which may lead to different diagnostic results. To solve these problems, computer aided diagnosis (CAD) systems have been attracting attention in recent years. One of the CAD systems is the temporal subtraction image technology. In this paper, we propose an image alignment method for generating temporal subtraction images from images taken before and after contrast agent was administered to the cervical lymph nodes of the same subject. In addition, we propose an image analysis method that suppresses overextraction of lymph node candidate regions on the temporal subtraction image based on the features of lymph nodes. We applied the proposed method to the CT images of three sets and compared the temporal subtraction images with the final lymph node extraction images, and confirmed that the proposed method can suppress the overextraction of lymph node regions.","PeriodicalId":411064,"journal":{"name":"2021 21st International Conference on Control, Automation and Systems (ICCAS)","volume":"163 4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132227631","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 : 2021-10-12DOI: 10.23919/ICCAS52745.2021.9649973
Leonid Kostrykin, Claus Rohr, K. Rohr
Large-scale image stitching of temporal video data acquired by a small robot can facilitate the inspection process of electric generators, reduce the inspection time, and improve the reliability. However, the image data poses a number of challenges due to the small field of view, lack of distinct texture, specular highlights, and other image artifacts. We introduce a novel image stitching method, which generates composite images of generator wedges from temporal videos using intensity-based registration and non-linear blending. In contrast to previous intensity-based registration approaches, our global method simultaneously exploits the information of all image frames of a video and directly determines the global image translations. We propose a suitable energy function and employ a graph-based method for globally optimal minimization in linear runtime. Regularization is used to exploit physical knowledge about the application domain which improves the robustness. We have applied our approach to temporal video data of rotor wedges and performed a comparison with previous methods. We found that our method yields superior results.
{"title":"Globally Optimal and Scalable Video Image Stitching for Robotic Visual Inspection of Electric Generators","authors":"Leonid Kostrykin, Claus Rohr, K. Rohr","doi":"10.23919/ICCAS52745.2021.9649973","DOIUrl":"https://doi.org/10.23919/ICCAS52745.2021.9649973","url":null,"abstract":"Large-scale image stitching of temporal video data acquired by a small robot can facilitate the inspection process of electric generators, reduce the inspection time, and improve the reliability. However, the image data poses a number of challenges due to the small field of view, lack of distinct texture, specular highlights, and other image artifacts. We introduce a novel image stitching method, which generates composite images of generator wedges from temporal videos using intensity-based registration and non-linear blending. In contrast to previous intensity-based registration approaches, our global method simultaneously exploits the information of all image frames of a video and directly determines the global image translations. We propose a suitable energy function and employ a graph-based method for globally optimal minimization in linear runtime. Regularization is used to exploit physical knowledge about the application domain which improves the robustness. We have applied our approach to temporal video data of rotor wedges and performed a comparison with previous methods. We found that our method yields superior results.","PeriodicalId":411064,"journal":{"name":"2021 21st International Conference on Control, Automation and Systems (ICCAS)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133589572","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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