mlsanityData to 7 Oct 2026

Antipodal Robotic Grasping using Generative Residual Convolutional Neural Network

arXiv 1909.04810 ↗First posted 11 Sep 2019cs.RO cs.CVcited by 59

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Abstract (arXiv)

In this paper, we present a modular robotic system to tackle the problem of generating and performing antipodal robotic grasps for unknown objects from n-channel image of the scene. We propose a novel Generative Residual Convolutional Neural Network (GR-ConvNet) model that can generate robust antipodal grasps from n-channel input at real-time speeds (~20ms). We evaluate the proposed model architecture on standard datasets and a diverse set of household objects. We achieved state-of-the-art accuracy of 97.7% and 94.6% on Cornell and Jacquard grasping datasets respectively. We also demonstrate a grasp success rate of 95.4% and 93% on household and adversarial objects respectively using a 7 DoF robotic arm.

Key facts. Cited by 59 papers in the map (data through 7 Oct 2026). First posted on arXiv 11 Sep 2019.

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Citing papers per year: 2021: 10; 2022: 9; 2023: 10; 2024: 16; 2025: 10; 2026: 4.

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  1. 2021End-to-end Trainable Deep Neural Network for Robotic Grasp Detection and Semantic Segmentation from RGBcited by 44
  2. 2022Edge Grasp Network: A Graph-Based SE(3)-invariant Approach to Grasp Detectioncited by 34
  3. 2023Grasp-Anything: Large-scale Grasp Dataset from Foundation Modelscited by 33
  4. 2024Language-driven Grasp Detectioncited by 26
  5. 2023Language-guided Robot Grasping: CLIP-based Referring Grasp Synthesis in Cluttercited by 22
  6. 2024Language-Driven 6-DoF Grasp Detection Using Negative Prompt Guidancecited by 16
  7. 2024Spot-Compose: A Framework for Open-Vocabulary Object Retrieval and Drawer Manipulation in Point Cloudscited by 14
  8. 2024Towards Open-World Grasping with Large Vision-Language Modelscited by 13
  9. 2022When Transformer Meets Robotic Grasping: Exploits Context for Efficient Grasp Detectioncited by 12
  10. 2023On Robot Grasp Learning Using Equivariant Modelscited by 12
  11. 2024Efficient Heatmap-Guided 6-Dof Grasp Detection in Cluttered Scenescited by 11
  12. 2021Simultaneous Multi-View Object Recognition and Grasping in Open-Ended Domainscited by 10
38 more
  1. 2023RGB-D Grasp Detection via Depth Guided Learning with Cross-modal Attentioncited by 9
  2. 2023SCENEREPLICA: Benchmarking Real-World Robot Manipulation by Creating Replicable Scenescited by 9
  3. 2024Lightweight Language-driven Grasp Detection using Conditional Consistency Modelcited by 9
  4. 2024Real-time object detection and robotic manipulation for agriculture using a YOLO-based learning approachcited by 7
  5. 2021A Hybrid Approach for Learning to Shift and Grasp with Elaborate Motion Primitivescited by 6
  6. 2021Learning suction graspability considering grasp quality and robot reachability for bin-pickingcited by 5
  7. 2024Robotic-CLIP: Fine-tuning CLIP on Action Data for Robotic Applicationscited by 5
  8. 2023GraNet: A Multi-Level Graph Network for 6-DoF Grasp Pose Generation in Cluttered Scenescited by 4
  9. 2024GraspMamba: A Mamba-based Language-driven Grasp Detection Framework with Hierarchical Feature Learningcited by 3
  10. 2021Double-Dot Network for Antipodal Grasp Detectioncited by 2
  11. 2021Lifelong 3D Object Recognition and Grasp Synthesis Using Dual Memory Recurrent Self-Organization Networkscited by 2
  12. 2022A Robotic Visual Grasping Design: Rethinking Convolution Neural Network with High-Resolutionscited by 2
  13. 2023Learning to Generate All Feasible Actionscited by 2
  14. 2024AGILE: Approach-based Grasp Inference Learned from Element Decompositioncited by 2
  15. 2024Show and Grasp: Few-shot Semantic Segmentation for Robot Grasping through Zero-shot Foundation Modelscited by 2
  16. 2024Language-driven Grasp Detection with Mask-guided Attentioncited by 2
  17. 2024Target-Oriented Object Grasping via Multimodal Human Guidancecited by 2
  18. 2024HMT-Grasp: A Hybrid Mamba-Transformer Approach for Robot Grasping in Cluttered Environmentscited by 2
  19. 2025Corner-Grasp: Multi-Action Grasp Detection and Active Gripper Adaptation for Grasping in Cluttered Environmentscited by 2
  20. 2025VCoT-Grasp: Grasp Foundation Models with Visual Chain-of-Thought Reasoning for Language-driven Grasp Generationcited by 2
  21. 2021Lightweight Convolutional Neural Network with Gaussian-based Grasping Representation for Robotic Grasping Detectioncited by 1
  22. 2021Deep 6-DoF Tracking of Unknown Objects for Reactive Graspingcited by 1
  23. 2021GI-NNet & RGI-NNet: Development of Robotic Grasp Pose Models, Trainable with Large as well as Limited Labelled Training Datasets, under supervised and semi supervised paradigmscited by 1
  24. 2022Data-efficient learning of object-centric grasp preferencescited by 1
  25. 2022VGQ-CNN: Moving Beyond Fixed Cameras and Top-Grasps for Grasp Quality Predictioncited by 1
  26. 2023FViT-Grasp: Grasping Objects With Using Fast Vision Transformerscited by 1
  27. 2024DistillGrasp: Integrating Features Correlation with Knowledge Distillation for Depth Completion of Transparent Objectscited by 1
  28. 2025Language-Guided Grasp Detection with Coarse-to-Fine Learning for Robotic Manipulationcited by 1
  29. 2026RealVLG-R1: A Large-Scale Real-World Visual-Language Grounding Benchmark for Robotic Perception and Manipulationcited by 1
  30. 2021Learning 6DoF Grasping Using Reward-Consistent Demonstrationcited by 0
  31. 2022PEGG-Net: Pixel-Wise Efficient Grasp Generation in Complex Scenescited by 0
  32. 2022Evaluating Gaussian Grasp Maps for Generative Grasping Modelscited by 0
  33. 2022GP-net: Flexible Viewpoint Grasp Proposalcited by 0
  34. 2022Enhancing Interpretability and Interactivity in Robot Manipulation: A Neurosymbolic Approachcited by 0
  35. 2023A novel integrated method of detection-grasping for specific object based on the box coordinate matchingcited by 0
  36. 2023LocaliseBot: Multi-view 3D object localisation with differentiable rendering for robot graspingcited by 0
  37. 2024Robust Loss Functions for Object Grasping under Limited Ground Truthcited by 0
  38. 2025A Benchmarking Study of Vision-based Robotic Grasping Algorithmscited by 0

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