While the exploration for embodied AI has spanned multiple decades, it remains a persistent
challenge to endow agents with human-level intelligence, including perception, learning …

Embodied robots which can interact with their environment and neighbours are increasingly
being used as a test case to develop Artificial Intelligence. This creates a need for …

Large language models (LLMs) have gained increasing popularity in robotic task planning
due to their exceptional abilities in text analytics and generation, as well as their broad …

Bridging the gap between motion models and reality is crucial by using limited data to
deploy robots in the real world. Deep learning is expected to be generalized to diverse …

The advancement of foundation models, such as large language models (LLMs), vision-
language models (VLMs), diffusion models, and robotics foundation models (RFMs), has …

In recent years, studies have been actively conducted on combining large language models
(LLM) and robotics; however, most have not considered end-to-end feed-back in the robot …

The rapid evolution of industrial robot hardware has created a technological gap with
software, limiting its adoption. The software solutions proposed in recent years have yet to …

In recent years, automation has significantly advanced the automobile manufacturing
industry. However, many tasks still involve human intervention, so there is a demand for the …

Large Language Models (LLMs) have unlocked new opportunities in processing non-
structured information. However, integrating LLM into conventional applications poses …

This study proposes a method for generating complex, long-horizon off-line task plans using
large language models (LLMs). Although several studies have been conducted in recent …