# Improved Trust in Human-Robot Collaboration with ChatGPT

arXiv: https://arxiv.org/abs/2304.12529 · HTML: https://mlsanity.com/paper/2304.12529/

## Key facts

- Cited by 18 papers in the map (data through 14 Oct 2026).
- Builds on 3 of its 35 references that are in the map.
- First posted on arXiv 25 Apr 2023.

## Builds on (most cited first, 3 of 3)

- [Few-Shot Parameter-Efficient Fine-Tuning is Better and Cheaper than In-Context Learning](https://mlsanity.com/paper/2205.05638/) (2022)
- [Cooperative Inverse Reinforcement Learning](https://mlsanity.com/paper/1606.03137/) (2016)
- [GPTs are GPTs: An Early Look at the Labor Market Impact Potential of Large Language Models](https://mlsanity.com/paper/2303.10130/) (2023)

## Built on by (most cited first, 18 of 18)

- [A Comprehensive Overview of Large Language Models](https://mlsanity.com/paper/2307.06435/) (2023)
- ["It's a Fair Game", or Is It? Examining How Users Navigate Disclosure Risks and Benefits When Using LLM-Based Conversational Agents](https://mlsanity.com/paper/2309.11653/) (2023)
- [LLM-Driven Robots Risk Enacting Discrimination, Violence, and Unlawful Actions](https://mlsanity.com/paper/2406.08824/) (2024)
- [To Help or Not to Help: LLM-based Attentive Support for Human-Robot Group Interactions](https://mlsanity.com/paper/2403.12533/) (2024)
- [Testing the Depth of ChatGPT's Comprehension via Cross-Modal Tasks Based on ASCII-Art: GPT3.5's Abilities in Regard to Recognizing and Generating ASCII-Art Are Not Totally Lacking](https://mlsanity.com/paper/2307.16806/) (2023)
- [Dobby: A Conversational Service Robot Driven by GPT-4](https://mlsanity.com/paper/2310.06303/) (2023)
- [Natural Language Instructions for Intuitive Human Interaction with Robotic Assistants in Field Construction Work](https://mlsanity.com/paper/2307.04195/) (2023)
- [A Systematic Literature Review of Computer Vision Applications in Robotized Wire Harness Assembly](https://mlsanity.com/paper/2309.13744/) (2023)
- [Large Language Models Understand Layout](https://mlsanity.com/paper/2407.05750/) (2024)
- [Foundation Models for Autonomous Robots in Unstructured Environments](https://mlsanity.com/paper/2407.14296/) (2024)
- [Exploring Gen-AI applications in building research and industry: A review](https://mlsanity.com/paper/2410.01098/) (2024)
- [InteractiveIE: Towards Assessing the Strength of Human-AI Collaboration in Improving the Performance of Information Extraction](https://mlsanity.com/paper/2305.14659/) (2023)
- [Human-mediated Large Language Models for Robotic Intervention in Children with Autism Spectrum Disorders](https://mlsanity.com/paper/2402.00260/) (2024)
- [A Framework for Adapting Human-Robot Interaction to Diverse User Groups](https://mlsanity.com/paper/2410.11377/) (2024)
- [ChatGPT and U(X): A Rapid Review on Measuring the User Experience](https://mlsanity.com/paper/2503.15808/) (2025)
- [A Social Robot with Inner Speech for Dietary Guidance](https://mlsanity.com/paper/2505.08664/) (2025)
- [Using Natural Language for Human-Robot Collaboration in the Real World](https://mlsanity.com/paper/2508.11759/) (2025)
- [Zero-shot adaptable task planning for autonomous construction robots: a comparative study of lightweight single and multi-AI agent systems](https://mlsanity.com/paper/2601.14091/) (2026)

## Abstract (arXiv)

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.