• Corpus ID: 235683469

SimNet: Enabling Robust Unknown Object Manipulation from Pure Synthetic Data via Stereo

@inproceedings{Kollar2021SimNetER,
  title={SimNet: Enabling Robust Unknown Object Manipulation from Pure Synthetic Data via Stereo},
  author={Thomas Kollar and Michael Laskey and Kevin Stone and Brijen Thananjeyan and Mark Tjersland},
  booktitle={CoRL},
  year={2021}
}
: Robot manipulation of unknown objects in unstructured environments is a challenging problem due to the variety of shapes, materials, arrangements and lighting conditions. Even with large-scale real-world data collection, robust perception and manipulation of transparent and reflective objects across various lighting conditions remains challenging. To address these challenges we propose an approach to performing sim-to-real transfer of robotic perception. The underlying model, SimNet, is… 

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