mlsanityData to 7 Oct 2026

Robotic Grasping using Deep Reinforcement Learning

arXiv 2007.04499 ↗First posted 9 Jul 2020cs.ROcited by 27

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Abstract (arXiv)

In this work, we present a deep reinforcement learning based method to solve the problem of robotic grasping using visio-motor feedback. The use of a deep learning based approach reduces the complexity caused by the use of hand-designed features. Our method uses an off-policy reinforcement learning framework to learn the grasping policy. We use the double deep Q-learning framework along with a novel Grasp-Q-Network to output grasp probabilities used to learn grasps that maximize the pick success. We propose a visual servoing mechanism that uses a multi-view camera setup that observes the scene which contains the objects of interest. We performed experiments using a Baxter Gazebo simulated environment as well as on the actual robot. The results show that our proposed method outperforms the baseline Q-learning framework and increases grasping accuracy by adapting a multi-view model in comparison to a single-view model.

Key facts. Cited by 27 papers in the map (data through 7 Oct 2026). First posted on arXiv 9 Jul 2020.

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Citing papers per year: 2022: 6; 2023: 6; 2024: 6; 2025: 8; 2026: 1.

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  1. 2025HybridVLA: Collaborative Diffusion and Autoregression in a Unified Vision-Language-Action Modelcited by 176
  2. 2024RoboMIND: Benchmark on Multi-embodiment Intelligence Normative Data for Robot Manipulationcited by 166
  3. 2023ManipLLM: Embodied Multimodal Large Language Model for Object-Centric Robotic Manipulationcited by 157
  4. 2024RoboMamba: Efficient Vision-Language-Action Model for Robotic Reasoning and Manipulationcited by 102
  5. 2024Lift3D Foundation Policy: Lifting 2D Large-Scale Pretrained Models for Robust 3D Robotic Manipulationcited by 45
  6. 2025CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learningcited by 37
  7. 2025AC-DiT: Adaptive Coordination Diffusion Transformer for Mobile Manipulationcited by 21
  8. 2024A Self-Correcting Vision-Language-Action Model for Fast and Slow System Manipulationcited by 20
  9. 2025From Experts to a Generalist: Toward General Whole-Body Control for Humanoid Robotscited by 16
  10. 2026SG-VLA: Learning Spatially-Grounded Vision-Language-Action Models for Mobile Manipulationcited by 8
  11. 2022World Robot Challenge 2020 -- Partner Robot: A Data-Driven Approach for Room Tidying with Mobile Manipulatorcited by 5
  12. 2023ImageManip: Image-based Robotic Manipulation with Affordance-guided Next View Selectioncited by 5
15 more
  1. 2025A Survey of Reinforcement Learning for Optimization in Automationcited by 4
  2. 2022End-to-end Reinforcement Learning of Robotic Manipulation with Robust Keypoints Representationcited by 2
  3. 2022Efficient Representations of Object Geometry for Reinforcement Learning of Interactive Grasping Policiescited by 2
  4. 2023Using Implicit Behavior Cloning and Dynamic Movement Primitive to Facilitate Reinforcement Learning for Robot Motion Planningcited by 2
  5. 2024Towards Real-World Efficiency: Domain Randomization in Reinforcement Learning for Pre-Capture of Free-Floating Moving Targets by Autonomous Robotscited by 2
  6. 2024Bayesian optimization for robust robotic grasping using a sensorized compliant handcited by 2
  7. 2023State Representations as Incentives for Reinforcement Learning Agents: A Sim2Real Analysis on Robotic Graspingcited by 1
  8. 2022Benchmarking Deep Reinforcement Learning Algorithms for Vision-based Roboticscited by 0
  9. 2022GloCAL: Glocalized Curriculum-Aided Learning of Multiple Tasks with Application to Robotic Graspingcited by 0
  10. 2022Enhancing team performance with transfer-learning during real-world human-robot collaborationcited by 0
  11. 2023Few-Shot Image-to-Semantics Translation for Policy Transfer in Reinforcement Learningcited by 0
  12. 2023CRC-RL: A Novel Visual Feature Representation Architecture for Unsupervised Reinforcement Learningcited by 0
  13. 2025Toward Deployable Multi-Robot Collaboration via a Symbolically-Guided Decision Transformercited by 0
  14. 2025DeGuV: Depth-Guided Visual Reinforcement Learning for Generalization and Interpretability in Manipulationcited by 0
  15. 2025Taxonomy and Trends in Reinforcement Learning for Robotics and Control Systems: A Structured Reviewcited by 0