  The deployment of autonomous robots in various domains has raised significant
concerns about their trustworthiness and accountability. This study explores
the potential of Large Language Models (LLMs) in analyzing ROS 2 logs generated
by autonomous robots and proposes a framework for log analysis that categorizes
log files into different aspects. The study evaluates the performance of three
different language models in answering questions related to StartUp, Warning,
and PDDL logs. The results suggest that GPT 4, a transformer-based model,
outperforms other models, however, their verbosity is not enough to answer why
or how questions for all kinds of actors involved in the interaction.
