Learning Visual Affordances with Target-Orientated Deep Q-Network to Grasp Objects by Harnessing Environmental Fixtures-Reference-Cited by-同舟云学术

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Learning Visual Affordances with Target-Orientated Deep Q-Network to Grasp Objects by Harnessing Environmental Fixtures

Published:2021-05-30 Issue: Volume: Page:
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Container-title:2021 IEEE International Conference on Robotics and Automation (ICRA)
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Author:

Liang Hengyue,Lou Xibai,Yang Yang,Choi Changhyun

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9560720/9560666/09561737.pdf?arnumber=9561737

Cited by 14 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. Multi-Stage Reinforcement Learning for Non-Prehensile Manipulation;IEEE Robotics and Automation Letters;2024-07

2. Learning Extrinsic Dexterity with Parameterized Manipulation Primitives;2024 IEEE International Conference on Robotics and Automation (ICRA);2024-05-13

3. Attribute-Based Robotic Grasping With Data-Efficient Adaptation;IEEE Transactions on Robotics;2024

4. CCA-MTFCN: A Robotic Pushing-Grasping Collaborative Method Based on Deep Reinforcement Learning;Communications in Computer and Information Science;2023-11-05

5. Learning Bifunctional Push-Grasping Synergistic Strategy for Goal-Agnostic and Goal-Oriented Tasks;2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS);2023-10-01

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