{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,7]],"date-time":"2026-03-07T01:56:10Z","timestamp":1772848570719,"version":"3.50.1"},"reference-count":20,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2023,12,28]],"date-time":"2023-12-28T00:00:00Z","timestamp":1703721600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China under Grant","doi-asserted-by":"publisher","award":["U20A20197"],"award-info":[{"award-number":["U20A20197"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China under Grant","doi-asserted-by":"publisher","award":["2020JH2\/10100040"],"award-info":[{"award-number":["2020JH2\/10100040"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Provincial Key Research and Development for Liaoning","award":["U20A20197"],"award-info":[{"award-number":["U20A20197"]}]},{"name":"Provincial Key Research and Development for Liaoning","award":["2020JH2\/10100040"],"award-info":[{"award-number":["2020JH2\/10100040"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>This study introduces a parallel YOLO\u2013GG deep learning network for collaborative robot target recognition and grasping to enhance the efficiency and precision of visual classification and grasping for collaborative robots. First, the paper outlines the target classification and detection task, the grasping system of the robotic arm, and the dataset preprocessing method. The real-time recognition and grasping network can identify a diverse spectrum of unidentified objects and determine the target type and appropriate capture box. Secondly, we propose a parallel YOLO\u2013GG deep vision network based on YOLO and GG-CNN. Thirdly, the YOLOv3 network, pre-trained with the COCO dataset, identifies the object category and position, while the GG-CNN network, trained using the Cornell Grasping dataset, predicts the grasping pose and scale. This study presents the processes for generating a target\u2019s grasping frame and recognition type using GG-CNN and YOLO networks, respectively. This completes the investigation of parallel networks for target recognition and grasping in collaborative robots. Finally, the experimental results are evaluated on the self-constructed NEU-COCO dataset for target recognition and positional grasping. The speed of detection has improved by 14.1%, with an accuracy of 94%. This accuracy is 4.0% greater than that of YOLOv3. Experimental proof was obtained through a robot grasping actual objects.<\/jats:p>","DOI":"10.3390\/s24010195","type":"journal-article","created":{"date-parts":[[2023,12,28]],"date-time":"2023-12-28T11:44:57Z","timestamp":1703763897000},"page":"195","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":22,"title":["Object Recognition and Grasping for Collaborative Robots Based on Vision"],"prefix":"10.3390","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9918-3414","authenticated-orcid":false,"given":"Ruohuai","family":"Sun","sequence":"first","affiliation":[{"name":"College of Information Science and Engineering, Northeastern University, Shenyang 110819, China"},{"name":"SIASUN Robot & Automation Co., Ltd., Shenyang 110168, China"},{"name":"Faculty of Robot Science and Engineering, Northeastern University, Shenyang 110169, China"}]},{"given":"Chengdong","family":"Wu","sequence":"additional","affiliation":[{"name":"College of Information Science and Engineering, Northeastern University, Shenyang 110819, China"},{"name":"Faculty of Robot Science and Engineering, Northeastern University, Shenyang 110169, China"}]},{"given":"Xue","family":"Zhao","sequence":"additional","affiliation":[{"name":"Daniel L. Goodwin College of Business, Benedict University, Chicago, IL 60601, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8397-7260","authenticated-orcid":false,"given":"Bin","family":"Zhao","sequence":"additional","affiliation":[{"name":"College of Information Science and Engineering, Northeastern University, Shenyang 110819, China"},{"name":"SIASUN Robot & Automation Co., Ltd., Shenyang 110168, China"},{"name":"Faculty of Robot Science and Engineering, Northeastern University, Shenyang 110169, China"}]},{"given":"Yang","family":"Jiang","sequence":"additional","affiliation":[{"name":"Faculty of Robot Science and Engineering, Northeastern University, Shenyang 110169, China"}]}],"member":"1968","published-online":{"date-parts":[[2023,12,28]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Mohammed, M.Q., Kwek, L.C., Chua, S.C., Aljaloud, A.S., Al-Dhaqm, A., Al-Mekhlafi, Z.G., and Mohammed, B.A. (2021). 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