Language Models as Zero-Shot Trajectory Generators

Large Language Models (LLMs) have recently shown promise as high-level planners for robots when given access to a selection of low-level skills. However, it is often assumed that LLMs do not possess sufficient knowledge to be used for the low-level trajectories themselves. In this work, we address t...

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Bibliographic Details
Published in:	IEEE robotics and automation letters Vol. 9; no. 7; pp. 6728 - 6735
Main Authors:	Kwon, Teyun, Palo, Norman Di, Johns, Edward
Format:	Journal Article
Language:	English
Published:	Piscataway IEEE 01.07.2024 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	AI-based methods Artificial intelligence Big Data big data in robotics and automation Codes Deep learning deep learning in grasping and manipulation End effectors Grasping Large language models Manipulators Object detection Object recognition Robot control Robot kinematics Robotics Task analysis Trajectory Trajectory planning
ISSN:	2377-3766, 2377-3766
Online Access:	Get full text
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