Volumetric-based Contact Point Detection for 7-DoF Grasping
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Abstract (arXiv)
In this paper, we propose a novel grasp pipeline based on contact point detection on the truncated signed distance function (TSDF) volume to achieve closed-loop 7-degree-of-freedom (7-DoF) grasping on cluttered environments. The key aspects of our method are that 1) the proposed pipeline exploits the TSDF volume in terms of multi-view fusion, contact-point sampling and evaluation, and collision checking, which provides reliable and collision-free 7-DoF gripper poses with real-time performance; 2) the contact-based pose representation effectively eliminates the ambiguity introduced by the normal-based methods, which provides a more precise and flexible solution. Extensive simulated and real-robot experiments demonstrate that the proposed pipeline can select more antipodal and stable grasp poses and outperforms normal-based baselines in terms of the grasp success rate in both simulated and physical scenarios.
Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). First posted on arXiv 14 Sep 2022.
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Citing papers per year: 2022: 2; 2023: 1; 2024: 1; 2025: 1.
5 papers.
- 2025SuperDec: 3D Scene Decomposition with Superquadric Primitivescited by 21
- 2023Learning Any-View 6DoF Robotic Grasping in Cluttered Scenes via Neural Surface Renderingcited by 5
- 2022Efficient Representations of Object Geometry for Reinforcement Learning of Interactive Grasping Policiescited by 2
- 2024You Only Scan Once: A Dynamic Scene Reconstruction Pipeline for 6-DoF Robotic Grasping of Novel Objectscited by 2
- 2022GP-net: Flexible Viewpoint Grasp Proposalcited by 0
- 2025SuperDec: 3D Scene Decomposition with Superquadric Primitives1 Apr 2025
- 2024You Only Scan Once: A Dynamic Scene Reconstruction Pipeline for 6-DoF Robotic Grasping of Novel Objects4 Apr 2024
- 2023Learning Any-View 6DoF Robotic Grasping in Cluttered Scenes via Neural Surface Rendering12 Jun 2023
- 2022Efficient Representations of Object Geometry for Reinforcement Learning of Interactive Grasping Policies20 Nov 2022
- 2022GP-net: Flexible Viewpoint Grasp Proposal21 Sep 2022