Generative Expressive Robot Behaviors using Large Language Models-Reference-Cited by-同舟云学术

Generative Expressive Robot Behaviors using Large Language Models

Published:2024-03-11 Issue: Volume:35 Page:482-491
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Container-title:Proceedings of the 2024 ACM/IEEE International Conference on Human-Robot Interaction
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Author:

Mahadevan Karthik¹^ORCID,Chien Jonathan²^ORCID,Brown Noah²^ORCID,Xu Zhuo²^ORCID,Parada Carolina²^ORCID,Xia Fei²^ORCID,Zeng Andy²^ORCID,Takayama Leila³^ORCID,Sadigh Dorsa²^ORCID

Affiliation:

1. University of Toronto, Toronto, ON, Canada

2. Google Deepmind, Mountain View, CA, USA

3. Hoku Labs, Santa Cruz, CA, USA

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3610977.3634999

Reference48 articles.

1. Michael Ahn, Anthony Brohan, Noah Brown, Yevgen Chebotar, Omar Cortes, Byron David, Chelsea Finn, Chuyuan Fu, Keerthana Gopalakrishnan, Karol Hausman, et al. 2023. Do As I Can, Not As I Say: Grounding Language in Robotic Affordances. In Conference on Robot Learning. PMLR, 287--318.

2. A model for synthesizing a combined verbal and nonverbal behavior based on personality traits in human-robot interaction

3. Niklas Bergstrom, Takayuki Kanda, Takahiro Miyashita, Hiroshi Ishiguro, and Norihiro Hagita. 2008. Modeling of natural human-robot encounters. In 2008 ieee/rsj international conference on intelligent robots and systems. IEEE, 2623--2629.

4. Design and evaluation of an end-user friendly tool for robot programming

5. Iterative Design of a System for Programming Socially Interactive Service Robots

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