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Here, \u201cunknown\u201d means that there is no prior information on object models, such as template or database of the object. Firstly, an object to be manipulated is randomly selected by user prior to the visual servoing task execution. Then, the raw image information about the object can be obtained and used to train a randomized tree classifier online. Secondly, the current image features can be computed using the well-trained classifier. Finally, the visual controller can be designed according to the error of image feature, which is defined as the difference between the desired image features and current image features. Five visual positioning of unknown objects experiments, including 2D rigid object and 3D non-rigid object, are conducted on a MOTOMAN-SV3X six degree-of-freedom (DOF) manipulator robot. Experimental results show that the proposed scheme can effectively position an unknown object in complex natural scenes, such as occlusion and illumination changes. Furthermore, the developed robot visual servoing scheme has an excellent positioning accuracy within 0.05\u00a0mm positioning error.<\/jats:p>","DOI":"10.1007\/s10846-021-01516-w","type":"journal-article","created":{"date-parts":[[2021,12,20]],"date-time":"2021-12-20T23:29:21Z","timestamp":1640042961000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Visual Servoing of Unknown Objects for Family Service Robots"],"prefix":"10.1007","volume":"104","author":[{"given":"Jing","family":"Xin","sequence":"first","affiliation":[]},{"given":"Caixia","family":"Dong","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9731-5943","authenticated-orcid":false,"given":"Youmin","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Yumeng","family":"Yao","sequence":"additional","affiliation":[]},{"given":"Ailing","family":"Gong","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2021,12,21]]},"reference":[{"key":"1516_CR1","unstructured":"Huebner, K., Welke, K., Przybylski, M., Vahrenkamp, N., Asfour, T., Kragic, D., Dillmann, R.: Grasping known objects with humanoid robots: a box-based approach. 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