Language-Conditioned Robotic Manipulation with Fast and Slow Thinking Article Swipe
Minjie Zhu
,
Yichen Zhu
,
Jinming Li
,
Junjie Wen
,
Zhiyuan Xu
,
Zhengping Che
,
Chaomin Shen
,
Yaxin Peng
,
Dong Liu
,
Feifei Feng
,
Jian Tang
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2401.04181
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2401.04181
The language-conditioned robotic manipulation aims to transfer natural language instructions into executable actions, from simple pick-and-place to tasks requiring intent recognition and visual reasoning. Inspired by the dual process theory in cognitive science, which suggests two parallel systems of fast and slow thinking in human decision-making, we introduce Robotics with Fast and Slow Thinking (RFST), a framework that mimics human cognitive architecture to classify tasks and makes decisions on two systems based on instruction types. Our RFST consists of two key components: 1) an instruction discriminator to determine which system should be activated based on the current user instruction, and 2) a slow-thinking system that is comprised of a fine-tuned vision language model aligned with the policy networks, which allows the robot to recognize user intention or perform reasoning tasks. To assess our methodology, we built a dataset featuring real-world trajectories, capturing actions ranging from spontaneous impulses to tasks requiring deliberate contemplation. Our results, both in simulation and real-world scenarios, confirm that our approach adeptly manages intricate tasks that demand intent recognition and reasoning. The project is available at https://jlm-z.github.io/RSFT/
Related Topics
Concepts
Executable
Computer science
Cognitive architecture
Human–computer interaction
Process (computing)
Artificial intelligence
Robot
Robotics
Natural language
Dual (grammatical number)
Key (lock)
Cognition
Cognitive robotics
Discriminator
Programming language
Psychology
Computer security
Literature
Art
Telecommunications
Detector
Neuroscience
Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2401.04181
- https://arxiv.org/pdf/2401.04181
- OA Status
- green
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4390783878
All OpenAlex metadata
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- OpenAlex ID
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https://openalex.org/W4390783878Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.2401.04181Digital Object Identifier
- Title
-
Language-Conditioned Robotic Manipulation with Fast and Slow ThinkingWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2024Year of publication
- Publication date
-
2024-01-08Full publication date if available
- Authors
-
Minjie Zhu, Yichen Zhu, Jinming Li, Junjie Wen, Zhiyuan Xu, Zhengping Che, Chaomin Shen, Yaxin Peng, Dong Liu, Feifei Feng, Jian TangList of authors in order
- Landing page
-
https://arxiv.org/abs/2401.04181Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/2401.04181Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
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https://arxiv.org/pdf/2401.04181Direct OA link when available
- Concepts
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Executable, Computer science, Cognitive architecture, Human–computer interaction, Process (computing), Artificial intelligence, Robot, Robotics, Natural language, Dual (grammatical number), Key (lock), Cognition, Cognitive robotics, Discriminator, Programming language, Psychology, Computer security, Literature, Art, Telecommunications, Detector, NeuroscienceTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
0Total citation count in OpenAlex
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| publication_date | 2024-01-08 |
| publication_year | 2024 |
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