Leveraging Large Language Models for Adaptive Task Planning and Action Tuning in Robotic Sequential Tasks

This work introduces a novel framework that leverages large language models to enable robots to modify their motion strategies and select the most suitable task plans based on the context, enhancing adaptability through applying language model-derived contextual insights.