{"total":120,"rows":[{"id":"2102.02915","title":"How to Train Your Robot with Deep Reinforcement Learning; Lessons We've Learned","created":"2021-02-04","cited_by_count":213,"area":null},{"id":"2104.07267","title":"ContactOpt: Optimizing Contact to Improve Grasps","created":"2021-04-15","cited_by_count":139,"area":null},{"id":"2106.12534","title":"Coarse-to-Fine Q-attention: Efficient Learning for Visual Robotic Manipulation via Discretisation","created":"2021-06-23","cited_by_count":122,"area":null},{"id":"2104.01542","title":"Synergies Between Affordance and Geometry: 6-DoF Grasp Detection via Implicit Representations","created":"2021-04-04","cited_by_count":108,"area":null},{"id":"2105.14829","title":"Q-attention: Enabling Efficient Learning for Vision-based Robotic Manipulation","created":"2021-05-31","cited_by_count":85,"area":null},{"id":"2307.14326","title":"Waypoint-Based Imitation Learning for Robotic Manipulation","created":"2023-07-26","cited_by_count":61,"area":"offlinerl"},{"id":"2301.08556","title":"NeRF in the Palm of Your Hand: Corrective Augmentation for Robotics via Novel-View Synthesis","created":"2023-01-18","cited_by_count":57,"area":"offlinerl"},{"id":"2101.00443","title":"Semantics for Robotic Mapping, Perception and Interaction: A Survey","created":"2021-01-02","cited_by_count":56,"area":null},{"id":"2406.11142","title":"Graspness Discovery in Clutters for Fast and Accurate Grasp Detection","created":"2024-06-17","cited_by_count":48,"area":null},{"id":"2202.09400","title":"Equivariant Transporter Network","created":"2022-02-18","cited_by_count":46,"area":null},{"id":"2107.05287","title":"End-to-end Trainable Deep Neural Network for Robotic Grasp Detection and Semantic Segmentation from RGB","created":"2021-07-12","cited_by_count":44,"area":null},{"id":"2410.23004","title":"DexGraspNet 2.0: Learning Generative Dexterous Grasping in Large-scale Synthetic Cluttered Scenes","created":"2024-10-30","cited_by_count":44,"area":null},{"id":"2202.00732","title":"IFOR: Iterative Flow Minimization for Robotic Object Rearrangement","created":"2022-02-01","cited_by_count":42,"area":null},{"id":"2103.02184","title":"RGB Matters: Learning 7-DoF Grasp Poses on Monocular RGBD Images","created":"2021-03-03","cited_by_count":39,"area":null},{"id":"2211.00191","title":"Edge Grasp Network: A Graph-Based SE(3)-invariant Approach to Grasp Detection","created":"2022-10-31","cited_by_count":35,"area":null},{"id":"2408.04380","title":"Deep Generative Models in Robotics: A Survey on Learning from Multimodal Demonstrations","created":"2024-08-08","cited_by_count":35,"area":"offlinerl"},{"id":"2408.11537","title":"A Survey of Embodied Learning for Object-Centric Robotic Manipulation","created":"2024-08-21","cited_by_count":35,"area":null},{"id":"2207.05053","title":"Learning Continuous Grasping Function with a Dexterous Hand from Human Demonstrations","created":"2022-07-11","cited_by_count":34,"area":null},{"id":"2303.17592","title":"Learning Human-to-Robot Handovers from Point Clouds","created":"2023-03-30","cited_by_count":34,"area":null},{"id":"2309.09818","title":"Grasp-Anything: Large-scale Grasp Dataset from Foundation Models","created":"2023-09-18","cited_by_count":33,"area":null},{"id":"2401.12046","title":"Fourier Transporter: Bi-Equivariant Robotic Manipulation in 3D","created":"2024-01-22","cited_by_count":33,"area":null},{"id":"2105.14291","title":"Deep Learning on Monocular Object Pose Detection and Tracking: A Comprehensive Overview","created":"2021-05-29","cited_by_count":31,"area":null},{"id":"2103.04783","title":"DDGC: Generative Deep Dexterous Grasping in Clutter","created":"2021-03-08","cited_by_count":29,"area":null},{"id":"2305.17590","title":"Integrating Action Knowledge and LLMs for Task Planning and Situation Handling in Open Worlds","created":"2023-05-27","cited_by_count":26,"area":null},{"id":"2406.09489","title":"Language-driven Grasp Detection","created":"2024-06-13","cited_by_count":26,"area":"diffusion"},{"id":"2204.13998","title":"Learning High-DOF Reaching-and-Grasping via Dynamic Representation of Gripper-Object Interaction","created":"2022-04-03","cited_by_count":24,"area":null},{"id":"2304.08587","title":"Grounding Classical Task Planners via Vision-Language Models","created":"2023-04-17","cited_by_count":23,"area":"mllm"},{"id":"2407.08366","title":"An Economic Framework for 6-DoF Grasp Detection","created":"2024-07-11","cited_by_count":23,"area":null},{"id":"2311.05779","title":"Language-guided Robot Grasping: CLIP-based Referring Grasp Synthesis in Clutter","created":"2023-11-09","cited_by_count":22,"area":null},{"id":"2212.05275","title":"Towards Scale Balanced 6-DoF Grasp Detection in Cluttered Scenes","created":"2022-12-10","cited_by_count":21,"area":null},{"id":"2112.02849","title":"DemoGrasp: Few-Shot Learning for Robotic Grasping with Human Demonstration","created":"2021-12-06","cited_by_count":20,"area":null},{"id":"2308.07948","title":"Leveraging Symmetries in Pick and Place","created":"2023-08-15","cited_by_count":19,"area":null},{"id":"2301.11564","title":"Learning 6-DoF Fine-grained Grasp Detection Based on Part Affordance Grounding","created":"2023-01-27","cited_by_count":17,"area":null},{"id":"2407.13842","title":"Language-Driven 6-DoF Grasp Detection Using Negative Prompt Guidance","created":"2024-07-18","cited_by_count":16,"area":null},{"id":"2406.18722","title":"Towards Open-World Grasping with Large Vision-Language Models","created":"2024-06-26","cited_by_count":15,"area":"mllm"},{"id":"2108.02425","title":"Simultaneous Semantic and Collision Learning for 6-DoF Grasp Pose Estimation","created":"2021-08-05","cited_by_count":14,"area":null},{"id":"2406.17659","title":"DKPROMPT: Domain Knowledge Prompting Vision-Language Models for Open-World Planning","created":"2024-06-25","cited_by_count":14,"area":"mllm"},{"id":"2312.08240","title":"CenterGrasp: Object-Aware Implicit Representation Learning for Simultaneous Shape Reconstruction and 6-DoF Grasp Estimation","created":"2023-12-13","cited_by_count":13,"area":null},{"id":"2312.11243","title":"GraspLDM: Generative 6-DoF Grasp Synthesis using Latent Diffusion Models","created":"2023-12-18","cited_by_count":13,"area":"diffusion"},{"id":"2504.10857","title":"ZeroGrasp: Zero-Shot Shape Reconstruction Enabled Robotic Grasping","created":"2025-04-15","cited_by_count":13,"area":null},{"id":"2306.06489","title":"On Robot Grasp Learning Using Equivariant Models","created":"2023-06-10","cited_by_count":12,"area":null},{"id":"2403.18546","title":"Efficient Heatmap-Guided 6-Dof Grasp Detection in Cluttered Scenes","created":"2024-03-27","cited_by_count":12,"area":null},{"id":"2104.14118","title":"REGRAD: A Large-Scale Relational Grasp Dataset for Safe and Object-Specific Robotic Grasping in Clutter","created":"2021-04-29","cited_by_count":11,"area":null},{"id":"2404.01727","title":"Generalizing 6-DoF Grasp Detection via Domain Prior Knowledge","created":"2024-04-02","cited_by_count":11,"area":null},{"id":"2106.01866","title":"Simultaneous Multi-View Object Recognition and Grasping in Open-Ended Domains","created":"2021-06-03","cited_by_count":10,"area":null},{"id":"2204.00134","title":"Model Predictive Control for Fluid Human-to-Robot Handovers","created":"2022-03-31","cited_by_count":9,"area":null},{"id":"2204.12471","title":"Coarse-to-fine Q-attention with Tree Expansion","created":"2022-04-26","cited_by_count":9,"area":null},{"id":"2302.14264","title":"RGB-D Grasp Detection via Depth Guided Learning with Cross-modal Attention","created":"2023-02-28","cited_by_count":9,"area":null},{"id":"2306.15620","title":"SCENEREPLICA: Benchmarking Real-World Robot Manipulation by Creating Replicable Scenes","created":"2023-06-27","cited_by_count":9,"area":null},{"id":"2310.08565","title":"Security Considerations in AI-Robotics: A Survey of Current Methods, Challenges, and Opportunities","created":"2023-10-12","cited_by_count":9,"area":null},{"id":"2402.05655","title":"Real-time Holistic Robot Pose Estimation with Unknown States","created":"2024-02-08","cited_by_count":9,"area":null},{"id":"2407.17967","title":"Lightweight Language-driven Grasp Detection using Conditional Consistency Model","created":"2024-07-25","cited_by_count":9,"area":"diffusion"},{"id":"2203.02119","title":"GraspARL: Dynamic Grasping via Adversarial Reinforcement Learning","created":"2022-03-04","cited_by_count":8,"area":null},{"id":"2411.05212","title":"RT-Grasp: Reasoning Tuning Robotic Grasping via Multi-modal Large Language Model","created":"2024-11-07","cited_by_count":7,"area":"lr"},{"id":"2101.04781","title":"Transferring Experience from Simulation to the Real World for Precise Pick-And-Place Tasks in Highly Cluttered Scenes","created":"2021-01-12","cited_by_count":6,"area":null},{"id":"2112.12612","title":"Towards Disturbance-Free Visual Mobile Manipulation","created":"2021-12-17","cited_by_count":6,"area":null},{"id":"2309.12038","title":"Uncertainty-driven Exploration Strategies for Online Grasp Learning","created":"2023-09-21","cited_by_count":6,"area":null},{"id":"2109.14275","title":"Simulation-based Bayesian inference for multi-fingered robotic grasping","created":"2021-09-29","cited_by_count":5,"area":null},{"id":"2302.13375","title":"Perceiving Unseen 3D Objects by Poking the Objects","created":"2023-02-26","cited_by_count":5,"area":null},{"id":"2307.16488","title":"Model-free Grasping with Multi-Suction Cup Grippers for Robotic Bin Picking","created":"2023-07-31","cited_by_count":5,"area":null},{"id":"2409.17727","title":"Robotic-CLIP: Fine-tuning CLIP on Action Data for Robotic Applications","created":"2024-09-26","cited_by_count":5,"area":"mllm"},{"id":"2205.04026","title":"I Know What You Draw: Learning Grasp Detection Conditioned on a Few Freehand Sketches","created":"2022-05-09","cited_by_count":4,"area":null},{"id":"2312.03345","title":"GraNet: A Multi-Level Graph Network for 6-DoF Grasp Pose Generation in Cluttered Scenes","created":"2023-12-06","cited_by_count":4,"area":null},{"id":"2107.13087","title":"DCL: Differential Contrastive Learning for Geometry-Aware Depth Synthesis","created":"2021-07-27","cited_by_count":3,"area":null},{"id":"2111.03987","title":"V-MAO: Generative Modeling for Multi-Arm Manipulation of Articulated Objects","created":"2021-11-07","cited_by_count":3,"area":null},{"id":"2402.05747","title":"Jacquard V2: Refining Datasets using the Human In the Loop Data Correction Method","created":"2024-02-08","cited_by_count":3,"area":null},{"id":"2409.14403","title":"GraspMamba: A Mamba-based Language-driven Grasp Detection Framework with Hierarchical Feature Learning","created":"2024-09-22","cited_by_count":3,"area":"ssm"},{"id":"2505.17389","title":"Bootstrapping Imitation Learning for Long-horizon Manipulation via Hierarchical Data Collection Space","created":"2025-05-23","cited_by_count":3,"area":"offlinerl"},{"id":"2107.01836","title":"GraspME -- Grasp Manifold Estimator","created":"2021-07-05","cited_by_count":2,"area":null},{"id":"2109.11544","title":"Lifelong 3D Object Recognition and Grasp Synthesis Using Dual Memory Recurrent Self-Organization Networks","created":"2021-09-23","cited_by_count":2,"area":null},{"id":"2112.14663","title":"MetaGraspNet_v0: A Large-Scale Benchmark Dataset for Vision-driven Robotic Grasping via Physics-based Metaverse Synthesis","created":"2021-12-29","cited_by_count":2,"area":null},{"id":"2209.01319","title":"Kinova Gemini: Interactive Robot Grasping with Visual Reasoning and Conversational AI","created":"2022-09-03","cited_by_count":2,"area":"lr"},{"id":"2209.07459","title":"A Robotic Visual Grasping Design: Rethinking Convolution Neural Network with High-Resolutions","created":"2022-09-15","cited_by_count":2,"area":null},{"id":"2301.12249","title":"Towards Precise Model-free Robotic Grasping with Sim-to-Real Transfer Learning","created":"2023-01-28","cited_by_count":2,"area":null},{"id":"2309.01055","title":"Integration of Vision-based Object Detection and Grasping for Articulated Manipulator in Lunar Conditions","created":"2023-09-03","cited_by_count":2,"area":null},{"id":"2402.14498","title":"A Collision-Aware Cable Grasping Method in Cluttered Environment","created":"2024-02-22","cited_by_count":2,"area":null},{"id":"2406.06460","title":"Towards Real-World Efficiency: Domain Randomization in Reinforcement Learning for Pre-Capture of Free-Floating Moving Targets by Autonomous Robots","created":"2024-06-10","cited_by_count":2,"area":"deeprl"},{"id":"2407.15771","title":"Local Occupancy-Enhanced Object Grasping with Multiple Triplanar Projection","created":"2024-07-22","cited_by_count":2,"area":null},{"id":"2407.19877","title":"Language-driven Grasp Detection with Mask-guided Attention","created":"2024-07-29","cited_by_count":2,"area":null},{"id":"2408.11138","title":"Target-Oriented Object Grasping via Multimodal Human Guidance","created":"2024-08-20","cited_by_count":2,"area":null},{"id":"2412.07487","title":"Stereo Hand-Object Reconstruction for Human-to-Robot Handover","created":"2024-12-10","cited_by_count":2,"area":null},{"id":"2502.01773","title":"Coarse-to-Fine 3D Keyframe Transporter","created":"2025-02-03","cited_by_count":2,"area":"offlinerl"},{"id":"2503.16013","title":"GraspCoT: Integrating Physical Property Reasoning for 6-DoF Grasping under Flexible Language Instructions","created":"2025-03-20","cited_by_count":2,"area":"lr"},{"id":"2505.03702","title":"Self-Supervised Learning for Robotic Leaf Manipulation: A Hybrid Geometric-Neural Approach","created":"2025-05-06","cited_by_count":2,"area":null},{"id":"2510.05827","title":"VCoT-Grasp: Grasp Foundation Models with Visual Chain-of-Thought Reasoning for Language-driven Grasp Generation","created":"2025-10-07","cited_by_count":2,"area":"lr"},{"id":"2103.00268","title":"Text-driven object affordance for guiding grasp-type recognition in multimodal robot teaching","created":"2021-02-27","cited_by_count":1,"area":null},{"id":"2103.05401","title":"Deep 6-DoF Tracking of Unknown Objects for Reactive Grasping","created":"2021-03-09","cited_by_count":1,"area":null},{"id":"2107.07452","title":"GI-NNet \\& RGI-NNet: Development of Robotic Grasp Pose Models, Trainable with Large as well as Limited Labelled Training Datasets, under supervised and semi supervised paradigms","created":"2021-07-15","cited_by_count":1,"area":null},{"id":"2203.00384","title":"Data-efficient learning of object-centric grasp preferences","created":"2022-03-01","cited_by_count":1,"area":null},{"id":"2210.00858","title":"Enhancing Interpretability and Interactivity in Robot Manipulation: A Neurosymbolic Approach","created":"2022-10-03","cited_by_count":1,"area":"lr"},{"id":"2304.08840","title":"GoferBot: A Visual Guided Human-Robot Collaborative Assembly System","created":"2023-04-18","cited_by_count":1,"area":null},{"id":"2311.13986","title":"FViT-Grasp: Grasping Objects With Using Fast Vision Transformers","created":"2023-11-23","cited_by_count":1,"area":null},{"id":"2403.02495","title":"Pseudo-Labeling and Contextual Curriculum Learning for Online Grasp Learning in Robotic Bin Picking","created":"2024-03-04","cited_by_count":1,"area":null},{"id":"2410.01033","title":"Single-Shot Learning of Stable Dynamical Systems for Long-Horizon Manipulation Tasks","created":"2024-10-01","cited_by_count":1,"area":null},{"id":"2412.04052","title":"Learning Dual-Arm Push and Grasp Synergy in Dense Clutter","created":"2024-12-05","cited_by_count":1,"area":"deeprl"},{"id":"2512.21065","title":"Language-Guided Grasp Detection with Coarse-to-Fine Learning for Robotic Manipulation","created":"2025-12-24","cited_by_count":1,"area":null},{"id":"2603.14880","title":"RealVLG-R1: A Large-Scale Real-World Visual-Language Grounding Benchmark for Robotic Perception and Manipulation","created":"2026-03-16","cited_by_count":1,"area":null},{"id":"2606.08440","title":"GraspFoM: Towards Reconstruction-Driven Robotic Grasping with 3D Foundation Priors","created":"2026-06-07","cited_by_count":1,"area":null},{"id":"2609.27780","title":"Task-Prototype Guided Flow Matching for Few-Shot Generalization in Vision-Language Robot Manipulation","created":"2026-08-18","cited_by_count":1,"area":"diffusion"},{"id":"2111.10522","title":"Real-World Semantic Grasp Detection Based on Attention Mechanism","created":"2021-11-20","cited_by_count":0,"area":null}],"next_cursor":"100"}