SGTM 2.0: Autonomously Untangling Long Cables using Interactive Perception
Author:
Affiliation:
1. University of California,AUTOLAB,Berkeley
2. Toyota Research Institute (TRI)
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10160211/10160212/10160574.pdf?arnumber=10160574
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1. Learning to Rearrange Deformable Cables, Fabrics, and Bags with Goal-Conditioned Transporter Networks
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5. Learning Rope Manipulation Policies Using Dense Object Descriptors Trained on Synthetic Depth Data
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1. MovingCables: Moving Cable Segmentation Method and Dataset;IEEE Robotics and Automation Letters;2024-08
2. GenDOM: Generalizable One-shot Deformable Object Manipulation with Parameter-Aware Policy;2024 IEEE International Conference on Robotics and Automation (ICRA);2024-05-13
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