LLM_motion

Codebase for generating expressive robot motion with a large language model (LLM aka GPT-4)

Link to Research Paper

TBA

Main Files

This codebase uses the framework as described in our submitted paper. In this implimentation, the GPT-4 model is used. The main files in this repo are:

The Jupyter notebook used to generate the prompt and query the LLM:

https://github.com/liamreneroy/LLM_motion/blob/main/scripts/llm_to_motion.ipynb

The prompt structure used to query the LLM:

https://github.com/liamreneroy/LLM_motion/blob/main/media/sample_prompt.txt

Sample output from the LLM based on the prompt:

https://github.com/liamreneroy/LLM_motion/blob/main/media/sample_output.txt

The task and robot description presented to users in our user study:

https://github.com/liamreneroy/LLM_motion/blob/main/media/task_description.txt

The statistical analyses for our two hypotheses (H1, H2) are here:

https://github.com/liamreneroy/LLM_motion/blob/main/stats/

All the raw data collected throughout our study is here:

https://github.com/liamreneroy/LLM_motion/blob/main/data/

Packages to Install:

pygame (see this webpage ~ https://www.pygame.org/wiki/GettingStarted)
jupyterlab, numpy, termcolor, openpyxl, nbconvert-webpdf, openai, wandb

Either use:
--> sudo apt-get install <package_name>
--> python3 -m pip install <package_name>
--> conda install -c conda-forge <package_name>

Example using conda:
--> conda install -c conda-forge <package_name>

jupyterlab or notebook
numpy
termcolor
openpyxl
nbconvert-webpdf
openai wandb

Owner:

Liam Rene Roy [email protected] [email protected]