{"total":221,"rows":[{"id":"2405.05941","title":"Evaluating Real-World Robot Manipulation Policies in Simulation","created":"2024-05-09","cited_by_count":495,"area":null},{"id":"2103.14127","title":"Contact-GraspNet: Efficient 6-DoF Grasp Generation in Cluttered Scenes","created":"2021-03-25","cited_by_count":218,"area":null},{"id":"2107.14483","title":"ManiSkill: Generalizable Manipulation Skill Benchmark with Large-Scale Demonstrations","created":"2021-07-30","cited_by_count":197,"area":null},{"id":"2111.03043","title":"A System for General In-Hand Object Re-Orientation","created":"2021-11-04","cited_by_count":165,"area":null},{"id":"2302.12766","title":"Language-Driven Representation Learning for Robotics","created":"2023-02-24","cited_by_count":165,"area":null},{"id":"2207.09450","title":"Human-to-Robot Imitation in the Wild","created":"2022-07-19","cited_by_count":161,"area":null},{"id":"2210.00379","title":"NeRF: Neural Radiance Field in 3D Vision: A Comprehensive Review (Updated Post-Gaussian Splatting)","created":"2022-10-01","cited_by_count":158,"area":null},{"id":"2202.08227","title":"Ditto: Building Digital Twins of Articulated Objects from Interaction","created":"2022-02-16","cited_by_count":156,"area":null},{"id":"2104.07267","title":"ContactOpt: Optimizing Contact to Improve Grasps","created":"2021-04-15","cited_by_count":139,"area":null},{"id":"2311.01977","title":"RT-Trajectory: Robotic Task Generalization via Hindsight Trajectory Sketches","created":"2023-11-03","cited_by_count":133,"area":null},{"id":"2308.07931","title":"Distilled Feature Fields Enable Few-Shot Language-Guided Manipulation","created":"2023-07-27","cited_by_count":130,"area":null},{"id":"2403.03174","title":"MOKA: Open-World Robotic Manipulation through Mark-Based Visual Prompting","created":"2024-03-05","cited_by_count":129,"area":null},{"id":"2110.14217","title":"Dex-NeRF: Using a Neural Radiance Field to Grasp Transparent Objects","created":"2021-10-27","cited_by_count":119,"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":"2212.00922","title":"Navigating to Objects in the Real World","created":"2022-12-02","cited_by_count":106,"area":null},{"id":"2306.11565","title":"HomeRobot: Open-Vocabulary Mobile Manipulation","created":"2023-06-20","cited_by_count":106,"area":null},{"id":"2311.16098","title":"On Bringing Robots Home","created":"2023-11-27","cited_by_count":101,"area":null},{"id":"2104.02646","title":"gradSim: Differentiable simulation for system identification and visuomotor control","created":"2021-04-06","cited_by_count":100,"area":null},{"id":"2202.00164","title":"DexVIP: Learning Dexterous Grasping with Human Hand Pose Priors from Video","created":"2022-02-01","cited_by_count":89,"area":null},{"id":"2211.09423","title":"DexPoint: Generalizable Point Cloud Reinforcement Learning for Sim-to-Real Dexterous Manipulation","created":"2022-11-17","cited_by_count":84,"area":null},{"id":"2201.12716","title":"You Only Demonstrate Once: Category-Level Manipulation from Single Visual Demonstration","created":"2022-01-30","cited_by_count":81,"area":null},{"id":"2106.14440","title":"VAT-Mart: Learning Visual Action Trajectory Proposals for Manipulating 3D ARTiculated Objects","created":"2021-06-28","cited_by_count":80,"area":null},{"id":"2110.03655","title":"Augmenting Reinforcement Learning with Behavior Primitives for Diverse Manipulation Tasks","created":"2021-10-07","cited_by_count":78,"area":null},{"id":"2403.09637","title":"GaussianGrasper: 3D Language Gaussian Splatting for Open-vocabulary Robotic Grasping","created":"2024-03-14","cited_by_count":78,"area":null},{"id":"2110.06192","title":"Beyond Pick-and-Place: Tackling Robotic Stacking of Diverse Shapes","created":"2021-10-12","cited_by_count":71,"area":null},{"id":"2101.00443","title":"Semantics for Robotic Mapping, Perception and Interaction: A Survey","created":"2021-01-02","cited_by_count":56,"area":null},{"id":"2409.18121","title":"Robot See Robot Do: Imitating Articulated Object Manipulation with Monocular 4D Reconstruction","created":"2024-09-26","cited_by_count":54,"area":null},{"id":"2212.10428","title":"HouseCat6D -- A Large-Scale Multi-Modal Category Level 6D Object Perception Dataset with Household Objects in Realistic Scenarios","created":"2022-12-20","cited_by_count":53,"area":null},{"id":"2112.09120","title":"Human Hands as Probes for Interactive Object Understanding","created":"2021-12-16","cited_by_count":52,"area":null},{"id":"2310.05921","title":"Conformal Decision Theory: Safe Autonomous Decisions from Imperfect Predictions","created":"2023-10-09","cited_by_count":50,"area":null},{"id":"2109.09163","title":"CaTGrasp: Learning Category-Level Task-Relevant Grasping in Clutter from Simulation","created":"2021-09-19","cited_by_count":49,"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":"2409.05865","title":"Robot Utility Models: General Policies for Zero-Shot Deployment in New Environments","created":"2024-09-09","cited_by_count":44,"area":null},{"id":"2411.02704","title":"RT-Affordance: Affordances are Versatile Intermediate Representations for Robot Manipulation","created":"2024-11-05","cited_by_count":43,"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":"2109.14082","title":"Sample-Efficient Safety Assurances using Conformal Prediction","created":"2021-09-28","cited_by_count":41,"area":null},{"id":"2311.00926","title":"M2T2: Multi-Task Masked Transformer for Object-centric Pick and Place","created":"2023-11-02","cited_by_count":41,"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":"2110.00087","title":"Seeing Glass: Joint Point Cloud and Depth Completion for Transparent Objects","created":"2021-09-30","cited_by_count":39,"area":null},{"id":"2306.16605","title":"KITE: Keypoint-Conditioned Policies for Semantic Manipulation","created":"2023-06-29","cited_by_count":39,"area":null},{"id":"2107.13545","title":"Fully Autonomous Real-World Reinforcement Learning with Applications to Mobile Manipulation","created":"2021-07-28","cited_by_count":35,"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":"2401.12202","title":"OK-Robot: What Really Matters in Integrating Open-Knowledge Models for Robotics","created":"2024-01-22","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":"2103.12311","title":"SuctionNet-1Billion: A Large-Scale Benchmark for Suction Grasping","created":"2021-03-23","cited_by_count":32,"area":null},{"id":"2108.11092","title":"INVIGORATE: Interactive Visual Grounding and Grasping in Clutter","created":"2021-08-25","cited_by_count":32,"area":null},{"id":"2103.04783","title":"DDGC: Generative Deep Dexterous Grasping in Clutter","created":"2021-03-08","cited_by_count":29,"area":null},{"id":"2108.05675","title":"Learning Visual Affordance Grounding from Demonstration Videos","created":"2021-08-12","cited_by_count":25,"area":null},{"id":"2510.08807","title":"Humanoid Everyday: A Comprehensive Robotic Dataset for Open-World Humanoid Manipulation","created":"2025-10-09","cited_by_count":25,"area":null},{"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":"2209.13036","title":"MonoGraspNet: 6-DoF Grasping with a Single RGB Image","created":"2022-09-26","cited_by_count":24,"area":null},{"id":"2510.20808","title":"The Reality Gap in Robotics: Challenges, Solutions, and Best Practices","created":"2025-10-23","cited_by_count":24,"area":null},{"id":"2104.00492","title":"A Joint Network for Grasp Detection Conditioned on Natural Language Commands","created":"2021-04-01","cited_by_count":23,"area":null},{"id":"2209.00517","title":"The Neural Process Family: Survey, Applications and Perspectives","created":"2022-09-01","cited_by_count":23,"area":null},{"id":"2203.13733","title":"Blocks Assemble! Learning to Assemble with Large-Scale Structured Reinforcement Learning","created":"2022-03-15","cited_by_count":22,"area":null},{"id":"2209.14284","title":"DexTransfer: Real World Multi-fingered Dexterous Grasping with Minimal Human Demonstrations","created":"2022-09-28","cited_by_count":22,"area":null},{"id":"2212.05108","title":"Visuotactile Affordances for Cloth Manipulation with Local Control","created":"2022-12-09","cited_by_count":21,"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":"2307.12172","title":"Challenges for Monocular 6D Object Pose Estimation in Robotics","created":"2023-07-22","cited_by_count":21,"area":null},{"id":"2410.20220","title":"Neural Fields in Robotics: A Survey","created":"2024-10-26","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":"2106.16118","title":"SimNet: Enabling Robust Unknown Object Manipulation from Pure Synthetic Data via Stereo","created":"2021-06-30","cited_by_count":18,"area":null},{"id":"2303.16382","title":"ARMBench: An Object-centric Benchmark Dataset for Robotic Manipulation","created":"2023-03-29","cited_by_count":18,"area":null},{"id":"2304.09302","title":"CabiNet: Scaling Neural Collision Detection for Object Rearrangement with Procedural Scene Generation","created":"2023-04-18","cited_by_count":18,"area":null},{"id":"2306.05716","title":"Transferring Foundation Models for Generalizable Robotic Manipulation","created":"2023-06-09","cited_by_count":18,"area":null},{"id":"2107.05627","title":"Hierarchical Neural Dynamic Policies","created":"2021-07-12","cited_by_count":17,"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":"2401.09939","title":"ICGNet: A Unified Approach for Instance-Centric Grasping","created":"2024-01-18","cited_by_count":16,"area":null},{"id":"2502.16420","title":"AnyDexGrasp: General Dexterous Grasping for Different Hands with Human-level Learning Efficiency","created":"2025-02-23","cited_by_count":16,"area":null},{"id":"2211.14648","title":"Learning Visuo-Haptic Skewering Strategies for Robot-Assisted Feeding","created":"2022-11-26","cited_by_count":15,"area":null},{"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":"2112.10143","title":"RoboAssembly: Learning Generalizable Furniture Assembly Policy in a Novel Multi-robot Contact-rich Simulation Environment","created":"2021-12-19","cited_by_count":14,"area":null},{"id":"2205.02835","title":"Contact Points Discovery for Soft-Body Manipulations with Differentiable Physics","created":"2022-05-05","cited_by_count":14,"area":null},{"id":"2504.00420","title":"Think Small, Act Big: Primitive Prompt Learning for Lifelong Robot Manipulation","created":"2025-04-01","cited_by_count":14,"area":null},{"id":"2212.03175","title":"Learning Representations that Enable Generalization in Assistive Tasks","created":"2022-12-05","cited_by_count":13,"area":null},{"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":"2504.03177","title":"Detection Based Part-level Articulated Object Reconstruction from Single RGBD Image","created":"2025-04-04","cited_by_count":13,"area":null},{"id":"2504.10857","title":"ZeroGrasp: Zero-Shot Shape Reconstruction Enabled Robotic Grasping","created":"2025-04-15","cited_by_count":13,"area":null},{"id":"2202.11911","title":"When Transformer Meets Robotic Grasping: Exploits Context for Efficient Grasp Detection","created":"2022-02-24","cited_by_count":12,"area":null},{"id":"2203.11544","title":"Visuo-Haptic Object Perception for Robots: An Overview","created":"2022-03-22","cited_by_count":12,"area":null},{"id":"2207.02959","title":"NeuralGrasps: Learning Implicit Representations for Grasps of Multiple Robotic Hands","created":"2022-07-06","cited_by_count":12,"area":null},{"id":"2306.06489","title":"On Robot Grasp Learning Using Equivariant Models","created":"2023-06-10","cited_by_count":12,"area":null},{"id":"2104.00776","title":"Collision-Aware Target-Driven Object Grasping in Constrained Environments","created":"2021-04-01","cited_by_count":11,"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":"2109.08817","title":"Learning to Regrasp by Learning to Place","created":"2021-09-18","cited_by_count":11,"area":null},{"id":"2208.00408","title":"DA$^2$ Dataset: Toward Dexterity-Aware Dual-Arm Grasping","created":"2022-07-31","cited_by_count":11,"area":null},{"id":"2310.02219","title":"What do we learn from a large-scale study of pre-trained visual representations in sim and real environments?","created":"2023-10-03","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":"2503.12609","title":"VISO-Grasp: Vision-Language Informed Spatial Object-centric 6-DoF Active View Planning and Grasping in Clutter and Invisibility","created":"2025-03-16","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":"2203.10568","title":"Accelerating Integrated Task and Motion Planning with Neural Feasibility Checking","created":"2022-03-20","cited_by_count":10,"area":null},{"id":"2209.08752","title":"Keypoint-GraspNet: Keypoint-based 6-DoF Grasp Generation from the Monocular RGB-D input","created":"2022-09-19","cited_by_count":10,"area":null},{"id":"2205.08189","title":"Automatic Acquisition of a Repertoire of Diverse Grasping Trajectories through Behavior Shaping and Novelty Search","created":"2022-05-17","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":"2310.04517","title":"Domain Randomization for Sim2real Transfer of Automatically Generated Grasping Datasets","created":"2023-10-06","cited_by_count":9,"area":null},{"id":"2106.08497","title":"GKNet: grasp keypoint network for grasp candidates detection","created":"2021-06-16","cited_by_count":8,"area":null},{"id":"2207.03333","title":"FewSOL: A Dataset for Few-Shot Object Learning in Robotic Environments","created":"2022-07-06","cited_by_count":8,"area":null},{"id":"2301.07213","title":"SCARP: 3D Shape Completion in ARbitrary Poses for Improved Grasping","created":"2023-01-17","cited_by_count":8,"area":null},{"id":"2403.10760","title":"CORN: Contact-based Object Representation for Nonprehensile Manipulation of General Unseen Objects","created":"2024-03-16","cited_by_count":8,"area":null}],"next_cursor":"100"}