S. Sajjadi, M. M. H. Fallah, M. Mehrandezh, F. Janabi-Sharifi
{"title":"基于随机图像的视觉预测控制","authors":"S. Sajjadi, M. M. H. Fallah, M. Mehrandezh, F. Janabi-Sharifi","doi":"10.1109/CASE49439.2021.9551441","DOIUrl":null,"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":0.0000,"publicationDate":"2021-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"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\":null,\"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\":0.0000,\"publicationDate\":\"2021-08-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE 17th International Conference on Automation Science and Engineering (CASE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CASE49439.2021.9551441\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE 17th International Conference on Automation Science and Engineering (CASE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CASE49439.2021.9551441","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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.
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