Online Estimation of Articulated Objects with Factor Graphs using Vision and Proprioceptive Sensing Article Swipe
Russell Buchanan
,
Adrian Röfer
,
João Moura
,
Abhinav Valada
,
Sethu Vijayakumar
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2309.16343
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2309.16343
From dishwashers to cabinets, humans interact with articulated objects every day, and for a robot to assist in common manipulation tasks, it must learn a representation of articulation. Recent deep learning learning methods can provide powerful vision-based priors on the affordance of articulated objects from previous, possibly simulated, experiences. In contrast, many works estimate articulation by observing the object in motion, requiring the robot to already be interacting with the object. In this work, we propose to use the best of both worlds by introducing an online estimation method that merges vision-based affordance predictions from a neural network with interactive kinematic sensing in an analytical model. Our work has the benefit of using vision to predict an articulation model before touching the object, while also being able to update the model quickly from kinematic sensing during the interaction. In this paper, we implement a full system using shared autonomy for robotic opening of articulated objects, in particular objects in which the articulation is not apparent from vision alone. We implemented our system on a real robot and performed several autonomous closed-loop experiments in which the robot had to open a door with unknown joint while estimating the articulation online. Our system achieved an 80% success rate for autonomous opening of unknown articulated objects.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2309.16343
- https://arxiv.org/pdf/2309.16343
- OA Status
- green
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4387222325
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4387222325Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.2309.16343Digital Object Identifier
- Title
-
Online Estimation of Articulated Objects with Factor Graphs using Vision and Proprioceptive SensingWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-09-28Full publication date if available
- Authors
-
Russell Buchanan, Adrian Röfer, João Moura, Abhinav Valada, Sethu VijayakumarList of authors in order
- Landing page
-
https://arxiv.org/abs/2309.16343Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/2309.16343Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://arxiv.org/pdf/2309.16343Direct OA link when available
- Concepts
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Artificial intelligence, Computer science, Affordance, Computer vision, Articulation (sociology), Kinematics, Object (grammar), Representation (politics), Pose, Robot, Convolutional neural network, Human–computer interaction, Politics, Law, Political science, Classical mechanics, PhysicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.several | 178 |
| abstract_inverted_index.success | 204 |
| abstract_inverted_index.unknown | 192, 210 |
| abstract_inverted_index.achieved | 201 |
| abstract_inverted_index.apparent | 164 |
| abstract_inverted_index.autonomy | 148 |
| abstract_inverted_index.estimate | 53 |
| abstract_inverted_index.interact | 5 |
| abstract_inverted_index.learning | 30, 31 |
| abstract_inverted_index.objects, | 154 |
| abstract_inverted_index.objects. | 212 |
| abstract_inverted_index.possibly | 46 |
| abstract_inverted_index.powerful | 35 |
| abstract_inverted_index.touching | 120 |
| abstract_inverted_index.cabinets, | 3 |
| abstract_inverted_index.contrast, | 50 |
| abstract_inverted_index.implement | 142 |
| abstract_inverted_index.kinematic | 100, 133 |
| abstract_inverted_index.observing | 56 |
| abstract_inverted_index.performed | 177 |
| abstract_inverted_index.previous, | 45 |
| abstract_inverted_index.requiring | 61 |
| abstract_inverted_index.affordance | 40, 92 |
| abstract_inverted_index.analytical | 104 |
| abstract_inverted_index.autonomous | 179, 207 |
| abstract_inverted_index.estimating | 195 |
| abstract_inverted_index.estimation | 87 |
| abstract_inverted_index.particular | 156 |
| abstract_inverted_index.simulated, | 47 |
| abstract_inverted_index.articulated | 7, 42, 153, 211 |
| abstract_inverted_index.closed-loop | 180 |
| abstract_inverted_index.dishwashers | 1 |
| abstract_inverted_index.experiments | 181 |
| abstract_inverted_index.implemented | 169 |
| abstract_inverted_index.interacting | 67 |
| abstract_inverted_index.interactive | 99 |
| abstract_inverted_index.introducing | 84 |
| abstract_inverted_index.predictions | 93 |
| abstract_inverted_index.articulation | 54, 117, 161, 197 |
| abstract_inverted_index.experiences. | 48 |
| abstract_inverted_index.interaction. | 137 |
| abstract_inverted_index.manipulation | 19 |
| abstract_inverted_index.vision-based | 36, 91 |
| abstract_inverted_index.articulation. | 27 |
| abstract_inverted_index.representation | 25 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 5 |
| citation_normalized_percentile |