mlsanityData to 14 Oct 2026

6-DOF Grasping for Target-driven Object Manipulation in Clutter

arXiv 1912.03628 ↗First posted 8 Dec 2019cs.RO cs.CVcited by 70

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Abstract (arXiv)

Grasping in cluttered environments is a fundamental but challenging robotic skill. It requires both reasoning about unseen object parts and potential collisions with the manipulator. Most existing data-driven approaches avoid this problem by limiting themselves to top-down planar grasps which is insufficient for many real-world scenarios and greatly limits possible grasps. We present a method that plans 6-DOF grasps for any desired object in a cluttered scene from partial point cloud observations. Our method achieves a grasp success of 80.3%, outperforming baseline approaches by 17.6% and clearing 9 cluttered table scenes (which contain 23 unknown objects and 51 picks in total) on a real robotic platform. By using our learned collision checking module, we can even reason about effective grasp sequences to retrieve objects that are not immediately accessible. Supplementary video can be found at https://youtu.be/w0B5S-gCsJk.

Key facts. Cited by 70 papers in the map (data through 14 Oct 2026). First posted on arXiv 8 Dec 2019.

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Citing papers per year: 2021: 20; 2022: 10; 2023: 19; 2024: 11; 2025: 7; 2026: 3.

70 papers.

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  1. 2022Perceiver-Actor: A Multi-Task Transformer for Robotic Manipulationcited by 551
  2. 2021Habitat 2.0: Training Home Assistants to Rearrange their Habitatcited by 511
  3. 2021Contact-GraspNet: Efficient 6-DoF Grasp Generation in Cluttered Scenescited by 218
  4. 2021Where2Act: From Pixels to Actions for Articulated 3D Objectscited by 182
  5. 2022SE(3)-DiffusionFields: Learning smooth cost functions for joint grasp and motion optimization through diffusioncited by 127
  6. 2023HomeRobot: Open-Vocabulary Mobile Manipulationcited by 106
  7. 2021ManipulaTHOR: A Framework for Visual Object Manipulationcited by 102
  8. 2023GNFactor: Multi-Task Real Robot Learning with Generalizable Neural Feature Fieldscited by 99
  9. 2021BundleTrack: 6D Pose Tracking for Novel Objects without Instance or Category-Level 3D Modelscited by 87
  10. 2023NeRF in the Palm of Your Hand: Corrective Augmentation for Robotics via Novel-View Synthesiscited by 57
  11. 2022Motion Policy Networkscited by 55
  12. 2022StructDiffusion: Language-Guided Creation of Physically-Valid Structures using Unseen Objectscited by 50
38 more
  1. 2024DexDiffuser: Generating Dexterous Grasps with Diffusion Modelscited by 48
  2. 2021Unseen Object Amodal Instance Segmentation via Hierarchical Occlusion Modelingcited by 43
  3. 2023M2T2: Multi-Task Masked Transformer for Object-centric Pick and Placecited by 41
  4. 2024Deep Generative Models in Robotics: A Survey on Learning from Multimodal Demonstrationscited by 35
  5. 2024A Survey of Embodied Learning for Object-Centric Robotic Manipulationcited by 35
  6. 2021NeRP: Neural Rearrangement Planning for Unknown Objectscited by 34
  7. 2023A Joint Modeling of Vision-Language-Action for Target-oriented Grasping in Cluttercited by 34
  8. 2021INVIGORATE: Interactive Visual Grounding and Grasping in Cluttercited by 32
  9. 2025GraspGen: A Diffusion-based Framework for 6-DOF Grasping with On-Generator Trainingcited by 32
  10. 2021DDGC: Generative Deep Dexterous Grasping in Cluttercited by 29
  11. 2022Learning to Grasp the Ungraspable with Emergent Extrinsic Dexteritycited by 28
  12. 2021A Joint Network for Grasp Detection Conditioned on Natural Language Commandscited by 23
  13. 2024DNAct: Diffusion Guided Multi-Task 3D Policy Learningcited by 23
  14. 2023CabiNet: Scaling Neural Collision Detection for Object Rearrangement with Procedural Scene Generationcited by 18
  15. 2024ICGNet: A Unified Approach for Instance-Centric Graspingcited by 16
  16. 2024Language-Driven 6-DoF Grasp Detection Using Negative Prompt Guidancecited by 16
  17. 2021RICE: Refining Instance Masks in Cluttered Environments with Graph Neural Networkscited by 15
  18. 2024Towards Open-World Grasping with Large Vision-Language Modelscited by 15
  19. 2021Simultaneous Semantic and Collision Learning for 6-DoF Grasp Pose Estimationcited by 14
  20. 2023GraspLDM: Generative 6-DoF Grasp Synthesis using Latent Diffusion Modelscited by 13
  21. 2021Collision-Aware Target-Driven Object Grasping in Constrained Environmentscited by 11
  22. 2021REGRAD: A Large-Scale Relational Grasp Dataset for Safe and Object-Specific Robotic Grasping in Cluttercited by 11
  23. 2025VISO-Grasp: Vision-Language Informed Spatial Object-centric 6-DoF Active View Planning and Grasping in Clutter and Invisibilitycited by 11
  24. 2023Self-Supervised Unseen Object Instance Segmentation via Long-Term Robot Interactioncited by 10
  25. 2021Learning Visual Shape Control of Novel 3D Deformable Objects from Partial-View Point Cloudscited by 9
  26. 2021GKNet: grasp keypoint network for grasp candidates detectioncited by 8
  27. 2022Cluttered Food Grasping with Adaptive Fingers and Synthetic-Data Trained Object Detectioncited by 8
  28. 2022TransGrasp: Grasp Pose Estimation of a Category of Objects by Transferring Grasps from Only One Labeled Instancecited by 8
  29. 2021Towards Disturbance-Free Visual Mobile Manipulationcited by 6
  30. 2021Learning suction graspability considering grasp quality and robot reachability for bin-pickingcited by 5
  31. 2023Out of Sight, Still in Mind: Reasoning and Planning about Unobserved Objects with Video Tracking Enabled Memory Modelscited by 5
  32. 2023Graph learning in robotics: a surveycited by 5
  33. 2021Kit-Net: Self-Supervised Learning to Kit Novel 3D Objects into Novel 3D Cavitiescited by 4
  34. 2022Hybrid Physical Metric For 6-DoF Grasp Pose Detectioncited by 4
  35. 2023DeformerNet: Learning Bimanual Manipulation of 3D Deformable Objectscited by 4
  36. 2023SceneScore: Learning a Cost Function for Object Arrangementcited by 4
  37. 2023GraNet: A Multi-Level Graph Network for 6-DoF Grasp Pose Generation in Cluttered Scenescited by 4
  38. 2024Grasp Diffusion Network: Learning Grasp Generators from Partial Point Clouds with Diffusion Models in SO(3)xR3cited by 4

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