Improved Trust in Human-Robot Collaboration With ChatGPT

被引:30
|
作者
Ye, Yang [1 ]
You, Hengxu [1 ]
Du, Jing [1 ]
机构
[1] Univ Florida, Dept Civil & Coastal Engn, Gainesville, FL 32611 USA
基金
美国国家科学基金会;
关键词
ChatGPT; human factors; human-robot interaction; large language model; trust; AUTOMATION;
D O I
10.1109/ACCESS.2023.3282111
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Human-robot collaboration is becoming increasingly important as robots become more involved in various aspects of human life in the era of Artificial Intelligence. However, the issue of human operators' trust in robots remains a significant concern, primarily due to the lack of adequate semantic understanding and communication between humans and robots. The emergence of Large Language Models (LLMs), such as ChatGPT, provides an opportunity to develop an interactive, communicative, and robust human-robot collaboration approach. This paper explores the impact of ChatGPT on trust in a human-robot collaboration assembly task. This study designs a robot control system called RoboGPT using ChatGPT to control a 7-degree-of-freedom robot arm to help human operators fetch, and place tools, while human operators can communicate with and control the robot arm using natural language. A human-subject experiment showed that incorporating ChatGPT in robots significantly increased trust in human-robot collaboration, which can be attributed to the robot's ability to communicate more effectively with humans. Furthermore, ChatGPT's ability to understand the nuances of human language and respond appropriately helps to build a more natural and intuitive human-robot interaction. The findings of this study have significant implications for the development of trustworthy human-robot collaboration systems.
引用
收藏
页码:55748 / 55754
页数:7
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