GraspGen: A Diffusion-based Framework for 6-DOF Grasping with On-Generator Training
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Abstract (arXiv)
Grasping is a fundamental robot skill, yet despite significant research advancements, learning-based 6-DOF grasping approaches are still not turnkey and struggle to generalize across different embodiments and in-the-wild settings. We build upon the recent success on modeling the object-centric grasp generation process as an iterative diffusion process. Our proposed framework, GraspGen, consists of a DiffusionTransformer architecture that enhances grasp generation, paired with an efficient discriminator to score and filter sampled grasps. We introduce a novel and performant on-generator training recipe for the discriminator. To scale GraspGen to both objects and grippers, we release a new simulated dataset consisting of over 53 million grasps. We demonstrate that GraspGen outperforms prior methods in simulations with singulated objects across different grippers, achieves state-of-the-art performance on the FetchBench grasping benchmark, and performs well on a real robot with noisy visual observations.
Key facts. Cited by 32 papers in the map (data through 14 Oct 2026). Builds on 64 of its 78 references that are in the map. First posted on arXiv 17 Jul 2025.
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64 of 78 references.
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- 2021Volumetric Grasping Network: Real-time 6 DOF Grasp Detection in Cluttercited by 95
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50 most cited of 64 All 64 (JSON)
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Citing papers per year: 2025: 7; 2026: 25.
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- 2026Replanning Human-Robot Collaborative Tasks with Vision-Language Models via Semantic and Physical Dual-Correctioncited by 1
- 2026Robo-Harness K1: Harnessing Robot-Use Agents via Perception Augmentation24 Sep 2026
- 2026Replanning Human-Robot Collaborative Tasks with Vision-Language Models via Semantic and Physical Dual-Correction16 Feb 2026
- 2025OmniDexVLG: Learning Dexterous Grasp Generation from Vision Language Model-Guided Grasp Semantics, Taxonomy and Functional Affordance3 Dec 2025
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- 2025Grasp-MPC: Closed-Loop Visual Grasping via Value-Guided Model Predictive Controlcited by 1
- 2026Relation-Centric Open-Vocabulary 3D Gaussian Segmentationcited by 1
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- 2026Show, Don't Tell: Detecting Novel Objects by Watching Human Videoscited by 0
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12 most cited of 16 All 16 (JSON)
- 2026Continual Learning for 6-DoF Grasp Synthesis via Experience and Demonstrations1 Oct 2026
- 2026Meta-Ctrl: Guaranteed Plan Generation by Decoupling Syntactic and Semantic Constraints23 Aug 2026
- 2026GraRe: Grasp Candidate Re-Ranking for Frozen 6-DoF Grasp Detectors2 Aug 2026
- 2026Beyond Visual Grasping: Benchmarking Complex Grasping from Detection to Execution15 Jul 2026
- 2026Relation-Centric Open-Vocabulary 3D Gaussian Segmentation1 Jul 2026
- 2026Robust 3D Alignment of Generative Reconstructions via Partial Monocular Observations1 Jul 2026
- 2026DCGrasp: Distance-aware Controllable Grasp Generation29 Jun 2026
- 2026Human2Any: Human-to-Robot Transfer via Constraint-Aware Compositional Planning27 Jun 2026
- 2026ManiTwin: Scaling Data-Generation-Ready Digital Object Dataset to 100K17 Mar 2026
- 2026Show, Don't Tell: Detecting Novel Objects by Watching Human Videos13 Mar 2026
- 2026Emerging Extrinsic Dexterity in Cluttered Scenes via Dynamics-aware Policy Learning10 Mar 2026
- 2026NovaPlan: Zero-Shot Long-Horizon Manipulation via Closed-Loop Video Language Planning23 Feb 2026
12 newest of 16 All 16 (JSON)