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This algorithm can calculate the final predicted grasping bounding box without any additional architecture, which significantly improves the speed of grasp inferences. In this study, we added the force-closure condition so that the final grasping bounding box could achieve grasping stability in a physical sense. We experimentally demonstrated that deep model-treated object detection and grasping detection are the same tasks. We used transfer learning to improve the prediction accuracy of the grasping bounding box. In particular, the ResNet-101 network weights, which were originally used in object detection, were used to continue training with the Cornell dataset. In terms of grasping detection, we used the trained model weights that were originally used in object detection as the features of the to-be-grasped objects and fed them to the network for continuous training. For 2828 test images, this method achieved nearly 98% accuracy and a speed of 14\u201317 frames per second.<\/jats:p>","DOI":"10.1115\/1.4065311","type":"journal-article","created":{"date-parts":[[2024,4,15]],"date-time":"2024-04-15T16:53:55Z","timestamp":1713200035000},"update-policy":"https:\/\/doi.org\/10.1115\/crossmarkpolicy-asme","source":"Crossref","is-referenced-by-count":1,"title":["Enhancing Robotic Grasping Detection Accuracy With the R2CNN Algorithm and Force-Closure"],"prefix":"10.1115","volume":"24","author":[{"given":"Hsien-I","family":"Lin","sequence":"first","affiliation":[{"name":"National Yang Ming Chiao Tung University Institute of Electrical and Control Engineering, , Hsinchu 30010 , Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Muhammad Ahsan Fatwaddin","family":"Shodiq","sequence":"additional","affiliation":[{"name":"National Yang Ming Chiao Tung University Institute of Electrical and Control Engineering, , Hsinchu 30010 , Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hong-Qi","family":"Chu","sequence":"additional","affiliation":[{"name":"National Taipei University of Technology Graduate Institute of Automation Technology, , Taipei 30010 , Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"33","published-online":{"date-parts":[[2024,5,9]]},"reference":[{"issue":"2","key":"2024050913491322200_CIT0001","doi-asserted-by":"publisher","first-page":"021004","DOI":"10.1115\/1.4038954","article-title":"Handling Perception Uncertainty in Simulation-Based Singulation Planning for Robotic Bin Picking","volume":"18","author":"Kumbla","year":"2018","journal-title":"ASME J. 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