Action Image Representation: Learning Scalable Deep Grasping Policies with Zero Real World Data-Reference-Cited by-同舟云学术

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Action Image Representation: Learning Scalable Deep Grasping Policies with Zero Real World Data

Published:2020-05 Issue: Volume: Page:
ISSN:
Container-title:2020 IEEE International Conference on Robotics and Automation (ICRA)
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Author:

Khansari Mohi,Kappler Daniel,Luo Jianlan,Bingham Jeff,Kalakrishnan Mrinal

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9187508/9196508/09197415.pdf?arnumber=9197415

Cited by 13 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. Leveraging symmetries in pick and place;The International Journal of Robotics Research;2024-01-05

2. Gradient Based Grasp Pose Optimization on a NeRF that Approximates Grasp Success;Lecture Notes in Networks and Systems;2024

3. Grip-Vision: Enhancing Object Handling with Computer Vision-Based Grip Classification;2023 2nd International Conference on Futuristic Technologies (INCOFT);2023-11-24

4. Train What You Know – Precise Pick-and-Place with Transporter Networks;2023 IEEE International Conference on Robotics and Automation (ICRA);2023-05-29

5. Ditto in the House: Building Articulation Models of Indoor Scenes through Interactive Perception;2023 IEEE International Conference on Robotics and Automation (ICRA);2023-05-29

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