Pub Date : 2022-12-10DOI: 10.1109/ICSAI57119.2022.10005349
Huatao Li, Zhongyi Hu, MingZhe Hu, MingJun Hu
Pulmonary Embolism (PE) is a serious threat to human life and health due to its high incidence rate and mortality. It is important to detect PE in time for the treatment of the disease and recovery of patients. Computed Tomography (CT) images are often used for disease diagnosis in clinical practice. Existing lung CT image disease classification algorithms only focus on local information, resulting in low accuracy, To solve this problem, a network model (DR-SENet) based on receptive field amplification and attention mechanism is proposed to detect PE. Specifically, Resnet network is used as the backbone network to slow down gradient explosion and gradient disappearance. Channel attention mechanism is used to extract the weight information between feature channels to guide the network to focus on important feature information, At the same time, the receptive field amplification structure is introduced to enhance the feature extraction ability of the network, obtain more comprehensive features, and make up for the limitation of convolution operation focusing on local features. The method is tested on the open PE dataset–FUMPE. Through experiments, we found that our method obtained better index and improved the auxiliary diagnosis performance of pulmonary embolism.
{"title":"Detection of Pulmonary Embolism Based on Receptive Field Amplification and Attention Mechanism","authors":"Huatao Li, Zhongyi Hu, MingZhe Hu, MingJun Hu","doi":"10.1109/ICSAI57119.2022.10005349","DOIUrl":"https://doi.org/10.1109/ICSAI57119.2022.10005349","url":null,"abstract":"Pulmonary Embolism (PE) is a serious threat to human life and health due to its high incidence rate and mortality. It is important to detect PE in time for the treatment of the disease and recovery of patients. Computed Tomography (CT) images are often used for disease diagnosis in clinical practice. Existing lung CT image disease classification algorithms only focus on local information, resulting in low accuracy, To solve this problem, a network model (DR-SENet) based on receptive field amplification and attention mechanism is proposed to detect PE. Specifically, Resnet network is used as the backbone network to slow down gradient explosion and gradient disappearance. Channel attention mechanism is used to extract the weight information between feature channels to guide the network to focus on important feature information, At the same time, the receptive field amplification structure is introduced to enhance the feature extraction ability of the network, obtain more comprehensive features, and make up for the limitation of convolution operation focusing on local features. The method is tested on the open PE dataset–FUMPE. Through experiments, we found that our method obtained better index and improved the auxiliary diagnosis performance of pulmonary embolism.","PeriodicalId":339547,"journal":{"name":"2022 8th International Conference on Systems and Informatics (ICSAI)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125615845","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 : 2022-12-10DOI: 10.1109/ICSAI57119.2022.10005359
Xinye Zhao, Bo Yuan, Guangming Sun, Peng Liu
As the operational relationship between each operational element in the context of military information system is more complex and the operational data is more massive, several attempts have been made in the past years to effectively conduct semantic analysis and extract key knowledge information from Chinese operational planning statements. This paper proposes to examine this question with the aim of provoking a discussion on how to bring the sciences of operational planning statements and and sematic description together to fulfill the expected potential. A series of natural language processing techniques such as lexical analysis, phrase structure analysis, and dependent syntax analysis are used to resolve this conundrum, to realize the analysis and and extraction of operational planning statements, and to store and display the structured knowledge information in the database. A platform corresponding to the algorithm process is given to show the results of the algorithm and the final implementation results. The paper then presents some observations and areas for further research.
{"title":"Chinese Semantic Description Framework of Operational Planning Statements","authors":"Xinye Zhao, Bo Yuan, Guangming Sun, Peng Liu","doi":"10.1109/ICSAI57119.2022.10005359","DOIUrl":"https://doi.org/10.1109/ICSAI57119.2022.10005359","url":null,"abstract":"As the operational relationship between each operational element in the context of military information system is more complex and the operational data is more massive, several attempts have been made in the past years to effectively conduct semantic analysis and extract key knowledge information from Chinese operational planning statements. This paper proposes to examine this question with the aim of provoking a discussion on how to bring the sciences of operational planning statements and and sematic description together to fulfill the expected potential. A series of natural language processing techniques such as lexical analysis, phrase structure analysis, and dependent syntax analysis are used to resolve this conundrum, to realize the analysis and and extraction of operational planning statements, and to store and display the structured knowledge information in the database. A platform corresponding to the algorithm process is given to show the results of the algorithm and the final implementation results. The paper then presents some observations and areas for further research.","PeriodicalId":339547,"journal":{"name":"2022 8th International Conference on Systems and Informatics (ICSAI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130507082","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 : 2022-12-10DOI: 10.1109/ICSAI57119.2022.10005393
Chunhui Liu
In this paper, the problem of ideals is studied in bounded Heyting algebras by using the principle and method of fuzzy sets theory. The notions of fuzzy commutative and implicative ideals are introduced in bounded Heyting algebras and some of their properties and relations are investigated. Some equivalent characterizations are obtained of fuzzy commutative and fuzzy implicative ideals. At the same time, a necessary and sufficient condition for a fuzzy commutative ideal forms a fuzzy implicative ideal is proved.
{"title":"Fuzzy Commutative and Implicative ideals in Bounded Heyting Algebras","authors":"Chunhui Liu","doi":"10.1109/ICSAI57119.2022.10005393","DOIUrl":"https://doi.org/10.1109/ICSAI57119.2022.10005393","url":null,"abstract":"In this paper, the problem of ideals is studied in bounded Heyting algebras by using the principle and method of fuzzy sets theory. The notions of fuzzy commutative and implicative ideals are introduced in bounded Heyting algebras and some of their properties and relations are investigated. Some equivalent characterizations are obtained of fuzzy commutative and fuzzy implicative ideals. At the same time, a necessary and sufficient condition for a fuzzy commutative ideal forms a fuzzy implicative ideal is proved.","PeriodicalId":339547,"journal":{"name":"2022 8th International Conference on Systems and Informatics (ICSAI)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114503005","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 : 2022-12-10DOI: 10.1109/ICSAI57119.2022.10005387
Zhuoheng Ran, Haihan Sun
Millions of blindness and visual impairment cases are caused by damage to the loss of photoreceptor function. Existing experiments and research have shown that electrical stimulation mechanisms can be established through different medical hardware strategies to help visually impaired patients partially recover their vision. Firstly, this paper analyzes the physiological principles to introduce the role of hardware systems in advanced visually impaired treatment schemes. Then, based on worldwide research advances in medical systems for visually impaired treatment, the latest hardware strategies and engineering issues of several representative systems are evaluated and compared in detail. Finally, the development prospect of medical hardware in the medical system is summarized on this basis for more efficient progress.
{"title":"Hardware Strategies in Medical Systems for Visually Impaired Treatment","authors":"Zhuoheng Ran, Haihan Sun","doi":"10.1109/ICSAI57119.2022.10005387","DOIUrl":"https://doi.org/10.1109/ICSAI57119.2022.10005387","url":null,"abstract":"Millions of blindness and visual impairment cases are caused by damage to the loss of photoreceptor function. Existing experiments and research have shown that electrical stimulation mechanisms can be established through different medical hardware strategies to help visually impaired patients partially recover their vision. Firstly, this paper analyzes the physiological principles to introduce the role of hardware systems in advanced visually impaired treatment schemes. Then, based on worldwide research advances in medical systems for visually impaired treatment, the latest hardware strategies and engineering issues of several representative systems are evaluated and compared in detail. Finally, the development prospect of medical hardware in the medical system is summarized on this basis for more efficient progress.","PeriodicalId":339547,"journal":{"name":"2022 8th International Conference on Systems and Informatics (ICSAI)","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114515991","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 : 2022-12-10DOI: 10.1109/ICSAI57119.2022.10005346
Bochuan Song, Tongyang Liu, Jingtan Ma, Yude He, Hui Fu
Event extraction is a sub-task of information extraction in natural language processing by extracting relevant event information from unstructured text. In order to obtain the hot events related to electric power public opinion in a timely manner and assist electric power staff to make quick decisions, this article suggests a deep learning-based event extraction model for electric power public opinion, which is mainly composed of two parts, namely, an event detection model and an argumentative meta-role extraction model. The event detection model is further extracted by using the BLSTM model to obtain the specific event categories of electrical power viewpoint text, and the argumentative role extraction model is employed to extract the features of electric power opinion text by using the BLSTM-CRF model to obtain the argumentative roles included within the text. In this paper, we solve the problem of overlapping roles by using an innovative location indexing annotation method. Finally, the events contained in the power opinion text are extracted by the joint extraction of the event category and the theoretical roles. By conducting experimental tests, this research proposes a model with superior performance in terms of event extraction outcomes and accuracy rate..
{"title":"A Deep Learning-based Event Extraction Method in the Field of Electric Power Public Opinion","authors":"Bochuan Song, Tongyang Liu, Jingtan Ma, Yude He, Hui Fu","doi":"10.1109/ICSAI57119.2022.10005346","DOIUrl":"https://doi.org/10.1109/ICSAI57119.2022.10005346","url":null,"abstract":"Event extraction is a sub-task of information extraction in natural language processing by extracting relevant event information from unstructured text. In order to obtain the hot events related to electric power public opinion in a timely manner and assist electric power staff to make quick decisions, this article suggests a deep learning-based event extraction model for electric power public opinion, which is mainly composed of two parts, namely, an event detection model and an argumentative meta-role extraction model. The event detection model is further extracted by using the BLSTM model to obtain the specific event categories of electrical power viewpoint text, and the argumentative role extraction model is employed to extract the features of electric power opinion text by using the BLSTM-CRF model to obtain the argumentative roles included within the text. In this paper, we solve the problem of overlapping roles by using an innovative location indexing annotation method. Finally, the events contained in the power opinion text are extracted by the joint extraction of the event category and the theoretical roles. By conducting experimental tests, this research proposes a model with superior performance in terms of event extraction outcomes and accuracy rate..","PeriodicalId":339547,"journal":{"name":"2022 8th International Conference on Systems and Informatics (ICSAI)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121501692","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 : 2022-12-10DOI: 10.1109/ICSAI57119.2022.10005531
Chunyue Zhang, Kaichuang Wang, Jingkun Ai, Jiawang Chen, Kun Wang
Thermal conductivity is an important parameter for the thermal properties of seafloor sediments, and currently there are very few devices to measure it in situ. This paper presents a new method for measuring thermal conductivity which is convenient for computer calculation. Corresponding equipment has also been designed to include a data acquisition module controlled by a microcontroller and a data analysis module that can be used in a personal computer. The experiment proved the feasibility of the method and the convenience of the device.
{"title":"An intelligent sensor for deep-sea sediment thermal conductivity","authors":"Chunyue Zhang, Kaichuang Wang, Jingkun Ai, Jiawang Chen, Kun Wang","doi":"10.1109/ICSAI57119.2022.10005531","DOIUrl":"https://doi.org/10.1109/ICSAI57119.2022.10005531","url":null,"abstract":"Thermal conductivity is an important parameter for the thermal properties of seafloor sediments, and currently there are very few devices to measure it in situ. This paper presents a new method for measuring thermal conductivity which is convenient for computer calculation. Corresponding equipment has also been designed to include a data acquisition module controlled by a microcontroller and a data analysis module that can be used in a personal computer. The experiment proved the feasibility of the method and the convenience of the device.","PeriodicalId":339547,"journal":{"name":"2022 8th International Conference on Systems and Informatics (ICSAI)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129053281","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 : 2022-12-10DOI: 10.1109/ICSAI57119.2022.10005381
Litao Wu, JiaHeng Huang, QingGuo Kan, ZiQi Fan, Jiajing Li, Rui Xu, Bo Wang, Tao Meng
Human factors readiness level is a framework to define the level of readiness or maturity related to the availability and completeness of a given technology when used by humans. The existing human factors readiness level assessment methods are most rely on expert scoring and questionnaires, which are limited by more qualitative metrics but fewer quantitative metrics, as well as more subjective metrics evaluation but less objective metrics. In this paper we first propose an objective and quantitative metric with six human factors anchors and the scoring matrix for manned space products, along with a cognitive computing-based assessment system. In our system we use a formal method to efficiently and accurately understand and extract the human factors anchors in data packages of manned space products. Furthermore, we take advantage of cognitive reasoning models to predict human factors readiness level on the basic of history cases base and logic rules base. Two experiments are designed to compare the analysis performance of our system with that of manual evaluation, and the retrieval accuracy of our system with that of keyword based methods.
{"title":"A Cognitive Computing Based System for Human Factors Readiness Level Assessment in Manned Space Product Design","authors":"Litao Wu, JiaHeng Huang, QingGuo Kan, ZiQi Fan, Jiajing Li, Rui Xu, Bo Wang, Tao Meng","doi":"10.1109/ICSAI57119.2022.10005381","DOIUrl":"https://doi.org/10.1109/ICSAI57119.2022.10005381","url":null,"abstract":"Human factors readiness level is a framework to define the level of readiness or maturity related to the availability and completeness of a given technology when used by humans. The existing human factors readiness level assessment methods are most rely on expert scoring and questionnaires, which are limited by more qualitative metrics but fewer quantitative metrics, as well as more subjective metrics evaluation but less objective metrics. In this paper we first propose an objective and quantitative metric with six human factors anchors and the scoring matrix for manned space products, along with a cognitive computing-based assessment system. In our system we use a formal method to efficiently and accurately understand and extract the human factors anchors in data packages of manned space products. Furthermore, we take advantage of cognitive reasoning models to predict human factors readiness level on the basic of history cases base and logic rules base. Two experiments are designed to compare the analysis performance of our system with that of manual evaluation, and the retrieval accuracy of our system with that of keyword based methods.","PeriodicalId":339547,"journal":{"name":"2022 8th International Conference on Systems and Informatics (ICSAI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128500781","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 : 2022-12-10DOI: 10.1109/ICSAI57119.2022.10005479
Lei Xiao, Feiyan Nie, Jingjing Shao, Zhongyi Hu
Ship tracking is an important task of inland waterway video surveillance. Inland waterway scenes are complex. Generic algorithms applied directly to inland river scenes are susceptible to performance degradation due to boat occlusion, light changes, and water ripples. In this paper, we propose the ATSR-DCF (Self-adaptive Temporal and Spatial Regularization Discriminative Correlation Filter) algorithm to improve ship tracking performance using adaptive spatiotemporal regularization and ship position incremental information. First, ATSR-DCF gets the initial frame and initial spatial and temporal regularization weights to train the correlation filter. Second, input other video frames, compute the optimized spatial and temporal regularization weights and update the filter using the Alternating Direction Method of Multipliers (ADMM). Finally, obtaining video sequence position increments constrains the subsequent position for predicting the target ship. In order to evaluate the performance of ASTR-DCF, we perform experiments using our group’s inland waterway ship dataset. The results show that the ATSR-DCF tracking performance outperforms other comparative algorithms. The tracking success rate is 80.0% and the accuracy rate is 86.6%.
{"title":"The Correlation Filter with Adaptive Spatial and Temporal Regularization for Inland Ship Tracking","authors":"Lei Xiao, Feiyan Nie, Jingjing Shao, Zhongyi Hu","doi":"10.1109/ICSAI57119.2022.10005479","DOIUrl":"https://doi.org/10.1109/ICSAI57119.2022.10005479","url":null,"abstract":"Ship tracking is an important task of inland waterway video surveillance. Inland waterway scenes are complex. Generic algorithms applied directly to inland river scenes are susceptible to performance degradation due to boat occlusion, light changes, and water ripples. In this paper, we propose the ATSR-DCF (Self-adaptive Temporal and Spatial Regularization Discriminative Correlation Filter) algorithm to improve ship tracking performance using adaptive spatiotemporal regularization and ship position incremental information. First, ATSR-DCF gets the initial frame and initial spatial and temporal regularization weights to train the correlation filter. Second, input other video frames, compute the optimized spatial and temporal regularization weights and update the filter using the Alternating Direction Method of Multipliers (ADMM). Finally, obtaining video sequence position increments constrains the subsequent position for predicting the target ship. In order to evaluate the performance of ASTR-DCF, we perform experiments using our group’s inland waterway ship dataset. The results show that the ATSR-DCF tracking performance outperforms other comparative algorithms. The tracking success rate is 80.0% and the accuracy rate is 86.6%.","PeriodicalId":339547,"journal":{"name":"2022 8th International Conference on Systems and Informatics (ICSAI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128529881","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 : 2022-12-10DOI: 10.1109/ICSAI57119.2022.10005539
Yang Gao, Na Lv
Multi-target threat assessment is an important prerequisite for jamming resource allocation and operational preparations. The more accurate the threat assessment is, the better the effect of decision support will be. In the face of complex battlefield environment and massive data, enough threat assessment attributes are conducive to improving the accuracy and credibility of the threat assessment. However, it also generates a huge amount of computation, which may cause huge challenge for both hardware and software to get the required results in a limited time. Thus, an effective attribute reduction method is proposed. Firstly, enough evaluation attributes are selected for specific threat targets. The attributes are reduced by analytic network process (AHP), the minimum variance method is used to optimize the attribute data, and then the rough set theory is applied to further optimize the threat evaluation attributes. Finally, the rationality and effectiveness are illustrated by an example of air target threat assessment
{"title":"Multi-target Threat Assessment Method Based on An Effective Reduction Method","authors":"Yang Gao, Na Lv","doi":"10.1109/ICSAI57119.2022.10005539","DOIUrl":"https://doi.org/10.1109/ICSAI57119.2022.10005539","url":null,"abstract":"Multi-target threat assessment is an important prerequisite for jamming resource allocation and operational preparations. The more accurate the threat assessment is, the better the effect of decision support will be. In the face of complex battlefield environment and massive data, enough threat assessment attributes are conducive to improving the accuracy and credibility of the threat assessment. However, it also generates a huge amount of computation, which may cause huge challenge for both hardware and software to get the required results in a limited time. Thus, an effective attribute reduction method is proposed. Firstly, enough evaluation attributes are selected for specific threat targets. The attributes are reduced by analytic network process (AHP), the minimum variance method is used to optimize the attribute data, and then the rough set theory is applied to further optimize the threat evaluation attributes. Finally, the rationality and effectiveness are illustrated by an example of air target threat assessment","PeriodicalId":339547,"journal":{"name":"2022 8th International Conference on Systems and Informatics (ICSAI)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131478408","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 : 2022-12-10DOI: 10.1109/ICSAI57119.2022.10005366
J. Sa, Shuai Liu, X. Zhang, Yuyan Song, Ziang Hu
With a three-dimensional calibration ball as the calibration object, the binocular camera was fixed at the end of six-axis mechanical arm, the movement of the mechanical arm was controlled by the Eye-in-hand calibration method. The robotic arm is kept in different positions to acquire the point cloud data of standard ball through binocular camera, further calculate the 3-D coordinates of the calibration ball in space. The homogeneous transformation equation was used to establish a mathematical model, and the calibration matrix was solved. The final calibration error was within 0.2mm.
{"title":"Research on Hand-eye Calibration Method Based on Binocular Camera","authors":"J. Sa, Shuai Liu, X. Zhang, Yuyan Song, Ziang Hu","doi":"10.1109/ICSAI57119.2022.10005366","DOIUrl":"https://doi.org/10.1109/ICSAI57119.2022.10005366","url":null,"abstract":"With a three-dimensional calibration ball as the calibration object, the binocular camera was fixed at the end of six-axis mechanical arm, the movement of the mechanical arm was controlled by the Eye-in-hand calibration method. The robotic arm is kept in different positions to acquire the point cloud data of standard ball through binocular camera, further calculate the 3-D coordinates of the calibration ball in space. The homogeneous transformation equation was used to establish a mathematical model, and the calibration matrix was solved. The final calibration error was within 0.2mm.","PeriodicalId":339547,"journal":{"name":"2022 8th International Conference on Systems and Informatics (ICSAI)","volume":"2015 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132875637","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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