Lei Zhang, Junqiu Zuo, Xingtian Yao, Xingguo Zhang, Liguo Shuai
{"title":"A robot visual servo-based approach to the determination of next best views","authors":"Lei Zhang, Junqiu Zuo, Xingtian Yao, Xingguo Zhang, Liguo Shuai","doi":"10.1109/ICMA.2015.7237906","DOIUrl":null,"url":null,"abstract":"In automatic 3D reconstruction, determining next best view (NBV) is the key problem for continuous automatic view planning. The mass vector chain (MVC) is one of the classical methods, but it can only determine the NBV direction. A visual servo-based approach is proposed in this paper for determining the orientation and direction of NBV. In the proposed approach, the 2-1/2-D visual servoing is used and modified in which MVC method is employed for orientation control and the image-based visual servoing is employed for position control. The MVC method is used in an open-loop, which decreases the dimensionality of the image Jacobian. The experimental results show that the proposed method can guide the robot to the desire views automatically. The final 3D reconstruction surface of an object is basically complete, only with a few tiny blind areas due to too many concave small surface patches of the object.","PeriodicalId":286366,"journal":{"name":"2015 IEEE International Conference on Mechatronics and Automation (ICMA)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE International Conference on Mechatronics and Automation (ICMA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICMA.2015.7237906","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
In automatic 3D reconstruction, determining next best view (NBV) is the key problem for continuous automatic view planning. The mass vector chain (MVC) is one of the classical methods, but it can only determine the NBV direction. A visual servo-based approach is proposed in this paper for determining the orientation and direction of NBV. In the proposed approach, the 2-1/2-D visual servoing is used and modified in which MVC method is employed for orientation control and the image-based visual servoing is employed for position control. The MVC method is used in an open-loop, which decreases the dimensionality of the image Jacobian. The experimental results show that the proposed method can guide the robot to the desire views automatically. The final 3D reconstruction surface of an object is basically complete, only with a few tiny blind areas due to too many concave small surface patches of the object.