Learning to reason over scene graphs: a case study of finetuning GPT-2 into a robot language model for grounded task planning

Learning to reason over scene graphs: a case study of finetuning GPT-2 into a robot language model for grounded task planning

Long-horizon task planning is essential for the development of intelligent assistive and service robots. In this work, we investigate the applicability of a smaller class of large language models (LLMs), specifically GPT-2, in robotic task planning by learning to decompose tasks into subgoal specifi...

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Bibliographic Details
Main Authors: Georgia Chalvatzaki, Ali Younes, Daljeet Nandha, An Thai Le, Leonardo F. R. Ribeiro, Iryna Gurevych
Format: Article
Language:English
Published: Frontiers Media S.A. 2023-08-01
Series:Frontiers in Robotics and AI
Subjects:
robot learning
task planning
grounding
language models (LMs)
pretrained models
scene graphs
Online Access:https://www.frontiersin.org/articles/10.3389/frobt.2023.1221739/full

Internet

https://www.frontiersin.org/articles/10.3389/frobt.2023.1221739/full

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