In a rapidly evolving digital landscape autonomous tools and robots are
becoming commonplace. Recognizing the significance of this development, this
paper explores the integration of Large Language Models (LLMs) like Generative
pre-trained transformer (GPT) into human-robot teaming environments to
facilitate variable autonomy through the means of verbal human-robot
communication. In this paper, we introduce a novel framework for such a
GPT-powered multi-robot testbed environment, based on a Unity Virtual Reality
(VR) setting. This system allows users to interact with robot agents through
natural language, each powered by individual GPT cores. By means of OpenAI's
function calling, we bridge the gap between unstructured natural language input
and structure robot actions. A user study with 12 participants explores the
effectiveness of GPT-4 and, more importantly, user strategies when being given
the opportunity to converse in natural language within a multi-robot
environment. Our findings suggest that users may have preconceived expectations
on how to converse with robots and seldom try to explore the actual language
and cognitive capabilities of their robot collaborators. Still, those users who
did explore where able to benefit from a much more natural flow of
communication and human-like back-and-forth. We provide a set of lessons
learned for future research and technical implementations of similar systems.

该论文探讨了将大型语言模型（如生成式预训练变换器 GPT）整合到人机合作环境中，通过口头人机交流手段促进可变自主性的快速发展的数字景观中，介绍了一种基于 Unity 虚拟现实（VR）环境的 GPT 驱动多机器人测试平台的创新框架。用户研究表明，用户对于与机器人对话的预设期望较高，却很少尝试探索机器人合作伙伴的实际语言和认知能力，但那些进行探索的用户能从更自然的沟通和人类式的双向交流中受益。我们提供了一组对未来研究和类似系统的技术实施的经验教训。