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Conference Paper
Robot Manipulation Planning with Large Pre-Trained Models of Language, Vision, and Action
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- Authors
- Youngsung Son, Hyonyong Han, Junhee Park
- Issue Date
- 2024-10
- Citation
- International Conference on Information and Communication Technology Convergence (ICTC) 2024, pp.542-544
- Publisher
- IEEE
- Language
- English
- Type
- Conference Paper
- Abstract
- This paper explores the integration of large pre-trained models of language, vision, and action to enhance robot manipulation planning. By leveraging advanced language models such as GPT-4 and Gemini, task planning can be articulated in natural language, allowing for intuitive and precise task specifications. The paper describes task and motion planning (TAMP), which is crucial for robot operation, optimizing precise execution by considering the work environment and linking high-level decision-making with detailed motion control.
- KSP Keywords
- Language Model, Manipulation Planning, Motion Planning, Natural language, Robot manipulation, Task planning, decision making, motion control, work environment