{"total":31,"rows":[{"id":"2104.03304","title":"Hand-Object Contact Consistency Reasoning for Human Grasps Generation","created":"2021-04-07","cited_by_count":160,"area":null},{"id":"2209.12941","title":"End-to-End Affordance Learning for Robotic Manipulation","created":"2022-09-26","cited_by_count":57,"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":"2212.00338","title":"3D-Aware Object Goal Navigation via Simultaneous Exploration and Identification","created":"2022-12-01","cited_by_count":46,"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":"2504.18829","title":"Dexonomy: Synthesizing All Dexterous Grasp Types in a Grasp Taxonomy","created":"2025-04-26","cited_by_count":20,"area":null},{"id":"2208.03963","title":"MetaGraspNet: A Large-Scale Benchmark Dataset for Scene-Aware Ambidextrous Bin Picking via Physics-based Metaverse Synthesis","created":"2022-08-08","cited_by_count":13,"area":null},{"id":"2304.11196","title":"Fast GraspNeXt: A Fast Self-Attention Neural Network Architecture for Multi-task Learning in Computer Vision Tasks for Robotic Grasping on the Edge","created":"2023-04-21","cited_by_count":7,"area":null},{"id":"2305.16378","title":"Sim-Suction: Learning a Suction Grasp Policy for Cluttered Environments Using a Synthetic Benchmark","created":"2023-05-25","cited_by_count":7,"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":"2607.24744","title":"Data Pyramid for Embodied Manipulation: A Survey","created":"2026-07-27","cited_by_count":6,"area":null},{"id":"2111.02571","title":"Learning suction graspability considering grasp quality and robot reachability for bin-picking","created":"2021-11-04","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":"2201.08968","title":"Mechanical Search on Shelves using a Novel \"Bluction\" Tool","created":"2022-01-22","cited_by_count":3,"area":null},{"id":"2310.05717","title":"STOPNet: Multiview-based 6-DoF Suction Detection for Transparent Objects on Production Lines","created":"2023-10-09","cited_by_count":2,"area":null},{"id":"2409.19494","title":"OptiGrasp: Optimized Grasp Pose Detection Using RGB Images for Warehouse Picking Robots","created":"2024-09-29","cited_by_count":2,"area":null},{"id":"2504.01861","title":"Corner-Grasp: Multi-Action Grasp Detection and Active Gripper Adaptation for Grasping in Cluttered Environments","created":"2025-04-02","cited_by_count":2,"area":null},{"id":"2506.17110","title":"Monocular One-Shot Metric-Depth Alignment for RGB-Based Robot Grasping","created":"2025-06-20","cited_by_count":2,"area":null},{"id":"2304.10108","title":"Reinforcement Learning for Picking Cluttered General Objects with Dense Object Descriptors","created":"2023-04-20","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":"2502.07238","title":"Diffusion Suction Grasping with Large-Scale Parcel Dataset","created":"2025-02-11","cited_by_count":1,"area":null},{"id":"2506.09765","title":"Learning to Optimize Package Picking for Large-Scale, Real-World Robot Induction","created":"2025-06-11","cited_by_count":1,"area":null},{"id":"2506.10359","title":"Demonstrating Multi-Suction Item Picking at Scale via Multi-Modal Learning of Pick Success","created":"2025-06-12","cited_by_count":1,"area":null},{"id":"2210.10842","title":"MMRNet: Improving Reliability for Multimodal Object Detection and Segmentation for Bin Picking via Multimodal Redundancy","created":"2022-10-19","cited_by_count":0,"area":null},{"id":"2305.10580","title":"Sim-MEES: Modular End-Effector System Grasping Dataset for Mobile Manipulators in Cluttered Environments","created":"2023-05-17","cited_by_count":0,"area":null},{"id":"2510.09267","title":"Placeit! A Framework for Learning Robot Object Placement Skills","created":"2025-10-10","cited_by_count":0,"area":null},{"id":"2602.06504","title":"MultiGraspNet: A Multitask 3D Vision Model for Multi-gripper Robotic Grasping","created":"2026-02-06","cited_by_count":0,"area":null},{"id":"2606.20272","title":"Efficiently Linking Real Scenes with Synthetic Data Generation for AI-based Cognitive Robotics and Computer Vision Applications","created":"2026-06-18","cited_by_count":0,"area":null},{"id":"2607.14341","title":"Beyond Visual Grasping: Benchmarking Complex Grasping from Detection to Execution","created":"2026-07-15","cited_by_count":0,"area":null},{"id":"2607.17757","title":"Seg2Grasp: A Robust Modular Suction Grasping in Bin Picking","created":"2026-07-20","cited_by_count":0,"area":null},{"id":"2608.28246","title":"Training-free Suction Grasp Detection for Deformed Aseptic Cartons Using Vision-Language Models and Geometric Surface Scoring","created":"2026-08-28","cited_by_count":0,"area":null}],"next_cursor":null}