Transferring Experience from Simulation to the Real World for Precise Pick-And-Place Tasks in Highly Cluttered Scenes-Reference-Cited by-同舟云学术

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Transferring Experience from Simulation to the Real World for Precise Pick-And-Place Tasks in Highly Cluttered Scenes

Published:2020-10-24 Issue: Volume: Page:
ISSN:
Container-title:2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
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Author:

Kleeberger Kilian¹,Volk Markus¹,Moosmann Marius¹,Thiessenhusen Erik¹,Roth Florian¹,Bormann Richard¹,Huber Marco F.²

Affiliation:

1. Fraunhofer Institute for Manufacturing Engineering and Automation IPA,Department Robot and Assistive Systems,Stuttgart,Germany,70569

2. Fraunhofer Institute for Manufacturing Engineering and Automation IPA,Center for Cyber Cognitive Intelligence (CCI),Stuttgart,Germany,70569

Funder

Ministry of Education

Ministry of Economic Affairs

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9340668/9340635/09341709.pdf?arnumber=9341709

Cited by 11 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. SimPLE, a visuotactile method learned in simulation to precisely pick, localize, regrasp, and place objects;Science Robotics;2024-06-26

2. Sim-to-Real Grasp Detection with Global-to-Local RGB-D Adaptation;2024 IEEE International Conference on Robotics and Automation (ICRA);2024-05-13

3. Investigation of a single object shape for efficient learning in bin picking of multiple types of objects;Artificial Life and Robotics;2024-04-03

4. NG-Net: No-Grasp annotation grasp detection network for stacked scenes;Journal of Intelligent Manufacturing;2024-02-07

5. 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

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