mlsanityData to 7 Oct 2026

Closing the Loop for Robotic Grasping: A Real-time, Generative Grasp Synthesis Approach

arXiv 1804.05172 ↗First posted 14 Apr 2018cs.ROcited by 117

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Abstract (arXiv)

This paper presents a real-time, object-independent grasp synthesis method which can be used for closed-loop grasping. Our proposed Generative Grasping Convolutional Neural Network (GG-CNN) predicts the quality and pose of grasps at every pixel. This one-to-one mapping from a depth image overcomes limitations of current deep-learning grasping techniques by avoiding discrete sampling of grasp candidates and long computation times. Additionally, our GG-CNN is orders of magnitude smaller while detecting stable grasps with equivalent performance to current state-of-the-art techniques. The light-weight and single-pass generative nature of our GG-CNN allows for closed-loop control at up to 50Hz, enabling accurate grasping in non-static environments where objects move and in the presence of robot control inaccuracies. In our real-world tests, we achieve an 83% grasp success rate on a set of previously unseen objects with adversarial geometry and 88% on a set of household objects that are moved during the grasp attempt. We also achieve 81% accuracy when grasping in dynamic clutter.

Key facts. Cited by 117 papers in the map (data through 7 Oct 2026). First posted on arXiv 14 Apr 2018.

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Citing papers per year: 2021: 27; 2022: 17; 2023: 24; 2024: 26; 2025: 18; 2026: 5.

117 papers.

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  1. 2021How to Train Your Robot with Deep Reinforcement Learning; Lessons We've Learnedcited by 201
  2. 2021ContactOpt: Optimizing Contact to Improve Graspscited by 137
  3. 2021Coarse-to-Fine Q-attention: Efficient Learning for Visual Robotic Manipulation via Discretisationcited by 120
  4. 2021Synergies Between Affordance and Geometry: 6-DoF Grasp Detection via Implicit Representationscited by 107
  5. 2021Q-attention: Enabling Efficient Learning for Vision-based Robotic Manipulationcited by 85
  6. 2023Waypoint-Based Imitation Learning for Robotic Manipulationcited by 59
  7. 2021Semantics for Robotic Mapping, Perception and Interaction: A Surveycited by 56
  8. 2023NeRF in the Palm of Your Hand: Corrective Augmentation for Robotics via Novel-View Synthesiscited by 56
  9. 2024Graspness Discovery in Clutters for Fast and Accurate Grasp Detectioncited by 47
  10. 2021End-to-end Trainable Deep Neural Network for Robotic Grasp Detection and Semantic Segmentation from RGBcited by 44
  11. 2022Equivariant Transporter Networkcited by 44
  12. 2022IFOR: Iterative Flow Minimization for Robotic Object Rearrangementcited by 42
38 more
  1. 2024DexGraspNet 2.0: Learning Generative Dexterous Grasping in Large-scale Synthetic Cluttered Scenescited by 41
  2. 2021RGB Matters: Learning 7-DoF Grasp Poses on Monocular RGBD Imagescited by 38
  3. 2024Deep Generative Models in Robotics: A Survey on Learning from Multimodal Demonstrationscited by 35
  4. 2022Learning Continuous Grasping Function with a Dexterous Hand from Human Demonstrationscited by 34
  5. 2022Edge Grasp Network: A Graph-Based SE(3)-invariant Approach to Grasp Detectioncited by 34
  6. 2023Learning Human-to-Robot Handovers from Point Cloudscited by 34
  7. 2024A Survey of Embodied Learning for Object-Centric Robotic Manipulationcited by 34
  8. 2023Grasp-Anything: Large-scale Grasp Dataset from Foundation Modelscited by 33
  9. 2024Fourier Transporter: Bi-Equivariant Robotic Manipulation in 3Dcited by 32
  10. 2021Deep Learning on Monocular Object Pose Detection and Tracking: A Comprehensive Overviewcited by 31
  11. 2021DDGC: Generative Deep Dexterous Grasping in Cluttercited by 28
  12. 2023Integrating Action Knowledge and LLMs for Task Planning and Situation Handling in Open Worldscited by 26
  13. 2024Language-driven Grasp Detectioncited by 26
  14. 2022Learning High-DOF Reaching-and-Grasping via Dynamic Representation of Gripper-Object Interactioncited by 23
  15. 2023Grounding Classical Task Planners via Vision-Language Modelscited by 23
  16. 2024An Economic Framework for 6-DoF Grasp Detectioncited by 23
  17. 2023Language-guided Robot Grasping: CLIP-based Referring Grasp Synthesis in Cluttercited by 22
  18. 2022Towards Scale Balanced 6-DoF Grasp Detection in Cluttered Scenescited by 21
  19. 2021DemoGrasp: Few-Shot Learning for Robotic Grasping with Human Demonstrationcited by 20
  20. 2023Leveraging Symmetries in Pick and Placecited by 18
  21. 2023Learning 6-DoF Fine-grained Grasp Detection Based on Part Affordance Groundingcited by 17
  22. 2024Language-Driven 6-DoF Grasp Detection Using Negative Prompt Guidancecited by 16
  23. 2021Simultaneous Semantic and Collision Learning for 6-DoF Grasp Pose Estimationcited by 14
  24. 2024DKPROMPT: Domain Knowledge Prompting Vision-Language Models for Open-World Planningcited by 14
  25. 2023CenterGrasp: Object-Aware Implicit Representation Learning for Simultaneous Shape Reconstruction and 6-DoF Grasp Estimationcited by 13
  26. 2023GraspLDM: Generative 6-DoF Grasp Synthesis using Latent Diffusion Modelscited by 13
  27. 2024Towards Open-World Grasping with Large Vision-Language Modelscited by 13
  28. 2025ZeroGrasp: Zero-Shot Shape Reconstruction Enabled Robotic Graspingcited by 13
  29. 2023On Robot Grasp Learning Using Equivariant Modelscited by 12
  30. 2021REGRAD: A Large-Scale Relational Grasp Dataset for Safe and Object-Specific Robotic Grasping in Cluttercited by 11
  31. 2024Efficient Heatmap-Guided 6-Dof Grasp Detection in Cluttered Scenescited by 11
  32. 2024Generalizing 6-DoF Grasp Detection via Domain Prior Knowledgecited by 11
  33. 2021Simultaneous Multi-View Object Recognition and Grasping in Open-Ended Domainscited by 10
  34. 2022Model Predictive Control for Fluid Human-to-Robot Handoverscited by 9
  35. 2022Coarse-to-fine Q-attention with Tree Expansioncited by 9
  36. 2023RGB-D Grasp Detection via Depth Guided Learning with Cross-modal Attentioncited by 9
  37. 2023SCENEREPLICA: Benchmarking Real-World Robot Manipulation by Creating Replicable Scenescited by 9
  38. 2023Security Considerations in AI-Robotics: A Survey of Current Methods, Challenges, and Opportunitiescited by 9

50 most cited of 117 All 117 (JSON)