Visual Manipulation Relationship Detection based on Gated Graph Neural Network for Robotic Grasping

Author:

Ding Mengyuan1,Liu Yaxin1,Yang Chenjie1,Lan Xuguang1

Affiliation:

1. College of Artificial Intelligence, Institute of Artificial Intelligence and Robotics, Xi´an Jiaotong University,National Engineering Laboratory for Visual Information Applications,Xi'an,China,710049

Funder

National Key R&D Program of China under

NSFC

Publisher

IEEE

Cited by 9 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Gated Self Attention Network for Efficient Grasping of Target Objects in Stacked Scenarios;2024 IEEE International Conference on Real-time Computing and Robotics (RCAR);2024-06-24

2. Grasp Manipulation Relationship Detection based on Graph Sample and Aggregation;2024 IEEE International Conference on Robotics and Automation (ICRA);2024-05-13

3. MetaGraspNetV2: All-in-One Dataset Enabling Fast and Reliable Robotic Bin Picking via Object Relationship Reasoning and Dexterous Grasping;IEEE Transactions on Automation Science and Engineering;2024

4. KG-Planner: Knowledge-Informed Graph Neural Planning for Collaborative Manipulators;IEEE Transactions on Automation Science and Engineering;2024

5. Prioritized Planning for Target-Oriented Manipulation via Hierarchical Stacking Relationship Prediction;2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS);2023-10-01

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