Efficient Learning of Object Placement with Intra-Category Transfer Article Swipe
Adrian Röfer
,
Russell Buchanan
,
Max Argus
,
Sethu Vijayakumar
,
Abhinav Valada
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2411.03408
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2411.03408
Efficient learning from demonstration for long-horizon tasks remains an open challenge in robotics. While significant effort has been directed toward learning trajectories, a recent resurgence of object-centric approaches has demonstrated improved sample efficiency, enabling transferable robotic skills. Such approaches model tasks as a sequence of object poses over time. In this work, we propose a scheme for transferring observed object arrangements to novel object instances by learning these arrangements on canonical class frames. We then employ this scheme to enable a simple yet effective approach for training models from as few as five demonstrations to predict arrangements of a wide range of objects including tableware, cutlery, furniture, and desk spaces. We propose a method for optimizing the learned models to enable efficient learning of tasks such as setting a table or tidying up an office with intra-category transfer, even in the presence of distractors. We present extensive experimental results in simulation and on a real robotic system for table setting which, based on human evaluations, scored 73.3% compared to a human baseline. We make the code and trained models publicly available at https://oplict.cs.uni-freiburg.de.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2411.03408
- https://arxiv.org/pdf/2411.03408
- OA Status
- green
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4404354541
All OpenAlex metadata
Raw OpenAlex JSON
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https://openalex.org/W4404354541Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.2411.03408Digital Object Identifier
- Title
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Efficient Learning of Object Placement with Intra-Category TransferWork title
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preprintOpenAlex work type
- Language
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enPrimary language
- Publication year
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2024Year of publication
- Publication date
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2024-11-05Full publication date if available
- Authors
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Adrian Röfer, Russell Buchanan, Max Argus, Sethu Vijayakumar, Abhinav ValadaList of authors in order
- Landing page
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https://arxiv.org/abs/2411.03408Publisher landing page
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https://arxiv.org/pdf/2411.03408Direct link to full text PDF
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YesWhether a free full text is available
- OA status
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greenOpen access status per OpenAlex
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https://arxiv.org/pdf/2411.03408Direct OA link when available
- Concepts
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Shot (pellet), Object (grammar), Transfer (computing), Computer science, Artificial intelligence, Transfer of learning, One shot, Engineering, Materials science, Mechanical engineering, Parallel computing, MetallurgyTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
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10Other works algorithmically related by OpenAlex
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