Matches in SemOpenAlex for { <https://semopenalex.org/work/W4387303531> ?p ?o ?g. }
Showing items 1 to 85 of
85
with 100 items per page.
- W4387303531 abstract "End-to-end grasp detection networks show state-of-the-art grasp accuracy in the standard datasets; these datasets use oriented rectangles to represent grasp poses and evaluate based on intersection over union (IoU) score. However, the model trained on these datasets, while being able to accurately localize to the object itself, does not necessarily predict the robust grasp pose, as it does not take into account the geometric features of the object. In this paper, we propose a Grasp Refinement Algorithm using RGBD images, which constrains the grasping detection network to output more robust grasp poses by extracting shallow features (e.g., object central axis) of the target object. The grasp refinement algorithm mainly consists of a feature extraction module and a grasp refinement module. The feature extraction module extracts the central axis of the target object and the object skeleton based on the depth threshold, which are then fed sequentially into the grasp refinement module to optimize the grasp pose predicted by the grasp detection network. The proposed algorithm achieves state-of-the-art grasp detection accuracy on both the Cornell grasp dataset, the Jacquard grasp dataset, and a simulated grasp environment based on the YCB dataset, which shows that our algorithm outperforms its counterparts in terms of grasp robustness." @default.
- W4387303531 created "2023-10-04" @default.
- W4387303531 creator A5000732007 @default.
- W4387303531 creator A5009032328 @default.
- W4387303531 creator A5025487231 @default.
- W4387303531 creator A5042241049 @default.
- W4387303531 creator A5047737377 @default.
- W4387303531 creator A5049242358 @default.
- W4387303531 date "2023-02-01" @default.
- W4387303531 modified "2023-10-06" @default.
- W4387303531 title "Detection Refinement using Geometric Features for Robust Robotic Grasping" @default.
- W4387303531 cites W1510186039 @default.
- W4387303531 cites W1523686390 @default.
- W4387303531 cites W1820657498 @default.
- W4387303531 cites W2039367092 @default.
- W4387303531 cites W2123435073 @default.
- W4387303531 cites W2145023731 @default.
- W4387303531 cites W2395611524 @default.
- W4387303531 cites W2603737562 @default.
- W4387303531 cites W2953669419 @default.
- W4387303531 cites W2962875890 @default.
- W4387303531 cites W2967869116 @default.
- W4387303531 cites W2996642256 @default.
- W4387303531 cites W3130885760 @default.
- W4387303531 cites W3186077919 @default.
- W4387303531 cites W4280539895 @default.
- W4387303531 cites W4292978855 @default.
- W4387303531 doi "https://doi.org/10.1109/iscer58777.2023.00025" @default.
- W4387303531 hasPublicationYear "2023" @default.
- W4387303531 type Work @default.
- W4387303531 citedByCount "0" @default.
- W4387303531 crossrefType "proceedings-article" @default.
- W4387303531 hasAuthorship W4387303531A5000732007 @default.
- W4387303531 hasAuthorship W4387303531A5009032328 @default.
- W4387303531 hasAuthorship W4387303531A5025487231 @default.
- W4387303531 hasAuthorship W4387303531A5042241049 @default.
- W4387303531 hasAuthorship W4387303531A5047737377 @default.
- W4387303531 hasAuthorship W4387303531A5049242358 @default.
- W4387303531 hasConcept C104317684 @default.
- W4387303531 hasConcept C138885662 @default.
- W4387303531 hasConcept C153180895 @default.
- W4387303531 hasConcept C154945302 @default.
- W4387303531 hasConcept C171268870 @default.
- W4387303531 hasConcept C185592680 @default.
- W4387303531 hasConcept C199360897 @default.
- W4387303531 hasConcept C2776401178 @default.
- W4387303531 hasConcept C2781238097 @default.
- W4387303531 hasConcept C31972630 @default.
- W4387303531 hasConcept C41008148 @default.
- W4387303531 hasConcept C41895202 @default.
- W4387303531 hasConcept C52622490 @default.
- W4387303531 hasConcept C55493867 @default.
- W4387303531 hasConcept C63479239 @default.
- W4387303531 hasConceptScore W4387303531C104317684 @default.
- W4387303531 hasConceptScore W4387303531C138885662 @default.
- W4387303531 hasConceptScore W4387303531C153180895 @default.
- W4387303531 hasConceptScore W4387303531C154945302 @default.
- W4387303531 hasConceptScore W4387303531C171268870 @default.
- W4387303531 hasConceptScore W4387303531C185592680 @default.
- W4387303531 hasConceptScore W4387303531C199360897 @default.
- W4387303531 hasConceptScore W4387303531C2776401178 @default.
- W4387303531 hasConceptScore W4387303531C2781238097 @default.
- W4387303531 hasConceptScore W4387303531C31972630 @default.
- W4387303531 hasConceptScore W4387303531C41008148 @default.
- W4387303531 hasConceptScore W4387303531C41895202 @default.
- W4387303531 hasConceptScore W4387303531C52622490 @default.
- W4387303531 hasConceptScore W4387303531C55493867 @default.
- W4387303531 hasConceptScore W4387303531C63479239 @default.
- W4387303531 hasFunder F4320321001 @default.
- W4387303531 hasLocation W43873035311 @default.
- W4387303531 hasOpenAccess W4387303531 @default.
- W4387303531 hasPrimaryLocation W43873035311 @default.
- W4387303531 hasRelatedWork W165915117 @default.
- W4387303531 hasRelatedWork W1996690921 @default.
- W4387303531 hasRelatedWork W2080808138 @default.
- W4387303531 hasRelatedWork W2106333554 @default.
- W4387303531 hasRelatedWork W2129483190 @default.
- W4387303531 hasRelatedWork W2163296013 @default.
- W4387303531 hasRelatedWork W2657478029 @default.
- W4387303531 hasRelatedWork W3146859979 @default.
- W4387303531 hasRelatedWork W4224220472 @default.
- W4387303531 hasRelatedWork W4385312898 @default.
- W4387303531 isParatext "false" @default.
- W4387303531 isRetracted "false" @default.
- W4387303531 workType "article" @default.