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Alchemist: LLM-Aided End-User Development of Robot Applications.

Authors :
Karli, Ulas Berk
Chen, Juo-Tung
Antony, Victor Nikhil
Huang, Chien-Ming
Source :
ACM/IEEE International Conference on Human-Robot Interaction; Mar2024, p361-370, 10p
Publication Year :
2024

Abstract

Large Language Models (LLMs) have the potential to catalyze a paradigm shift in end-user robot programming---moving from the conventional process of user specifying programming logic to an iterative, collaborative process in which the user specifies desired program outcomes while LLM produces detailed specifications. We introduce a novel integrated development system, Alchemist, that leverages LLMs to empower end-users in creating, testing, and running robot programs using natural language inputs, aiming to reduce the required knowledge for developing robot applications. We present a detailed examination of our system design and provide an exploratory study involving true end-users to assess capabilities, usability, and limitations of our system. Through the design, development, and evaluation of our system, we derive a set of lessons learned from the use of LLMs in robot programming. We discuss how LLMs may be the next frontier for democratizing end-user development of robot applications. [ABSTRACT FROM AUTHOR]

Details

Language :
English
Database :
Complementary Index
Journal :
ACM/IEEE International Conference on Human-Robot Interaction
Publication Type :
Conference
Accession number :
179537352
Full Text :
https://doi.org/10.1145/3610977.3634969