GDN: A Coarse-To-Fine (C2F) Representation for End-To-End 6-DoF Grasp Detection
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Abstract (arXiv)
We proposed an end-to-end grasp detection network, Grasp Detection Network (GDN), cooperated with a novel coarse-to-fine (C2F) grasp representation design to detect diverse and accurate 6-DoF grasps based on point clouds. Compared to previous two-stage approaches which sample and evaluate multiple grasp candidates, our architecture is at least 20 times faster. It is also 8% and 40% more accurate in terms of the success rate in single object scenes and the complete rate in clutter scenes, respectively. Our method shows superior results among settings with different number of views and input points. Moreover, we propose a new AP-based metric which considers both rotation and transition errors, making it a more comprehensive evaluation tool for grasp detection models.
Key facts. Cited by 8 papers in the map (data through 14 Oct 2026). First posted on arXiv 21 Oct 2020.
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Citing papers per year: 2021: 2; 2022: 1; 2023: 4; 2024: 1.
8 papers.
- 2021OCID-Ref: A 3D Robotic Dataset with Embodied Language for Clutter Scene Groundingcited by 16
- 2024ICGNet: A Unified Approach for Instance-Centric Graspingcited by 16
- 2022Keypoint-GraspNet: Keypoint-based 6-DoF Grasp Generation from the Monocular RGB-D inputcited by 10
- 2021GKNet: grasp keypoint network for grasp candidates detectioncited by 8
- 2023Uncertainty-driven Exploration Strategies for Online Grasp Learningcited by 6
- 2023Learning Any-View 6DoF Robotic Grasping in Cluttered Scenes via Neural Surface Renderingcited by 5
- 2023Model-free Grasping with Multi-Suction Cup Grippers for Robotic Bin Pickingcited by 5
- 2023KGNv2: Separating Scale and Pose Prediction for Keypoint-based 6-DoF Grasp Synthesis on RGB-D inputcited by 4
- 2024ICGNet: A Unified Approach for Instance-Centric Grasping18 Jan 2024
- 2023Uncertainty-driven Exploration Strategies for Online Grasp Learning21 Sep 2023
- 2023Model-free Grasping with Multi-Suction Cup Grippers for Robotic Bin Picking31 Jul 2023
- 2023Learning Any-View 6DoF Robotic Grasping in Cluttered Scenes via Neural Surface Rendering12 Jun 2023
- 2023KGNv2: Separating Scale and Pose Prediction for Keypoint-based 6-DoF Grasp Synthesis on RGB-D input9 Mar 2023
- 2022Keypoint-GraspNet: Keypoint-based 6-DoF Grasp Generation from the Monocular RGB-D input19 Sep 2022
- 2021GKNet: grasp keypoint network for grasp candidates detection16 Jun 2021
- 2021OCID-Ref: A 3D Robotic Dataset with Embodied Language for Clutter Scene Grounding13 Mar 2021