ChatGPT Empowered Long-Step Robot Control in Various Environments: A Case Application
About
This paper demonstrates how OpenAI's ChatGPT can be used in a few-shot setting to convert natural language instructions into a sequence of executable robot actions. The paper proposes easy-to-customize input prompts for ChatGPT that meet common requirements in practical applications, such as easy integration with robot execution systems and applicability to various environments while minimizing the impact of ChatGPT's token limit. The prompts encourage ChatGPT to output a sequence of predefined robot actions, represent the operating environment in a formalized style, and infer the updated state of the operating environment. Experiments confirmed that the proposed prompts enable ChatGPT to act according to requirements in various environments, and users can adjust ChatGPT's output with natural language feedback for safe and robust operation. The proposed prompts and source code are open-source and publicly available at https://github.com/microsoft/ChatGPT-Robot-Manipulation-Prompts
Related benchmarks
| Task | Dataset | Result | Rank | |
|---|---|---|---|---|
| Dual-arm task planning | Agricultural Greenhouse Scene | TFR19.4 | 16 | |
| Dual-arm task planning | Kitchen Scene | TEI0.817 | 16 | |
| Dual-arm task planning | X-DAPT Easy Packages | TFR (Task Success Fraction)22.7 | 8 | |
| Dual-arm task planning | Office Scene | TEI1.024 | 8 | |
| Dual-arm task planning | X-DAPT Factory scene | TFR45 | 8 | |
| Dual-arm task planning | X-DAPT Easy Packages 1.0 (test) | TEI (Time)1.349 | 8 | |
| Dual-arm task planning | X-DAPT Hard Packages 1.0 (test) | TEI45.5 | 8 | |
| Dual-arm task planning | X-DAPT Office scene | TFR0.208 | 8 | |
| Embodied AI Task Planning | RoboTwin Supermarket Scene (test) | TEI1.02 | 8 | |
| Dual-arm task planning | X-DAPT Medium Packages | TFR13.1 | 8 |