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 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 human-robot
collaboration systems.

本研究探讨了 ChatGPT 对人机协作任务中人的信任的影响，通过设计了一个机器人控制系统 RoboGPT，使用 ChatGPT 来控制七个自由度机械臂，帮助人类操作员完成工具的获取和放置，并使用自然语言与人类交互，结果表明 ChatGPT 能够显著提高人机协作中的信任度，建立更自然和直观的人机交互。

通过 ChatGPT 提高人机协作的信任度

Improved Trust in Human-Robot Collaboration with ChatGPT

Robot-based assembly in construction has emerged as a promising solution to
address numerous challenges such as increasing costs, labor shortages, and the
demand for safe and efficient construction processes. One of the main obstacles
in realizing the full potential of these robotic systems is the need for
effective and efficient sequence planning for construction tasks. Current
approaches, including mathematical and heuristic techniques or machine learning
methods, face limitations in their adaptability and scalability to dynamic
construction environments. To expand the ability of the current robot system in
sequential understanding, this paper introduces RoboGPT, a novel system that
leverages the advanced reasoning capabilities of ChatGPT, a large language
model, for automated sequence planning in robot-based assembly applied to
construction tasks. The proposed system adapts ChatGPT for construction
sequence planning and demonstrate its feasibility and effectiveness through
experimental evaluation including Two case studies and 80 trials about real
construction tasks. The results show that RoboGPT-driven robots can handle
complex construction operations and adapt to changes on the fly. This paper
contributes to the ongoing efforts to enhance the capabilities and performance
of robot-based assembly systems in the construction industry, and it paves the
way for further integration of large language model technologies in the field
of construction robotics.

本论文详细介绍了 RoboGPT，使用大型语言模型 ChatGPT 的高级推理功能，实现了自动机器人流程规划，并通过两个实例的试验展示其可行性和有效性，推动了建筑行业机器人组装的进一步发展。