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Syst."],"published-print":{"date-parts":[[2022,8]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Grasp estimation is a fundamental technique crucial for robot manipulation tasks. In this work, we present a scene-oriented grasp estimation scheme taking constraints of the grasp pose imposed by the environment into consideration and training on samples satisfying the constraints. We formulate valid grasps for a parallel-jaw gripper as vectors in a two-dimensional (2D) image and detect them with a fully convolutional network that simultaneously estimates the vectors\u2019 origins and directions. The detected vectors are then converted to 6 degree-of-freedom (6-DOF) grasps with a tailored strategy. As such, the network is able to detect multiple grasp candidates from a cluttered scene in one shot using only an RGB image as input. We evaluate our approach on the GraspNet-1Billion dataset and archived comparable performance as state-of-the-art while being efficient in runtime.<\/jats:p>","DOI":"10.1007\/s40747-021-00459-x","type":"journal-article","created":{"date-parts":[[2021,7,27]],"date-time":"2021-07-27T14:55:00Z","timestamp":1627397700000},"page":"2911-2922","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["GraspVDN: scene-oriented grasp estimation by learning vector representations of grasps"],"prefix":"10.1007","volume":"8","author":[{"given":"Zhipeng","family":"Dong","sequence":"first","affiliation":[]},{"given":"Hongkun","family":"Tian","sequence":"additional","affiliation":[]},{"given":"Xuefeng","family":"Bao","sequence":"additional","affiliation":[]},{"given":"Yunhui","family":"Yan","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4397-0931","authenticated-orcid":false,"given":"Fei","family":"Chen","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2021,7,27]]},"reference":[{"key":"459_CR1","doi-asserted-by":"crossref","unstructured":"Stogl D, Zumkeller D, Navarro SE, Heilig A, Hein B (2017) Tracking, reconstruction and grasping of unknown rotationally symmetrical objects from a conveyor belt. 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