Building general-purpose robots that can operate seamlessly, in any environment, with any
object, and utilizing various skills to complete diverse tasks has been a long-standing goal in …

We survey applications of pretrained foundation models in robotics. Traditional deep
learning models in robotics are trained on small datasets tailored for specific tasks, which …

Recent developments in foundation models, like Large Language Models (LLMs) and Vision-
Language Models (VLMs), trained on extensive data, facilitate flexible application across …

Improving the generalization capabilities of general-purpose robotic agents has long been a
significant challenge actively pursued by research communities. Existing approaches often …

The proliferation of Large Language Models (LLMs) has s fueled a shift in robot learning
from automation towards general embodied Artificial Intelligence (AI). Adopting foundation …

Foundation models that incorporate language, vision, and more recently actions have
revolutionized the ability to harness internet scale data to reason about useful tasks …

Recent progress in vision language foundation models has shown their ability to understand
multimodal data and resolve complicated vision language tasks, including robotics …

Large language models (LLMs) have undergone significant expansion and have been
increasingly integrated across various domains. Notably, in the realm of robot task planning …

Foundation models pretrained on diverse data at scale have demonstrated extraordinary
capabilities in a wide range of vision and language tasks. When such models are deployed …

The burgeoning field of intelligent robotics demands the development of agile and versatile
agents that can effectively navigate and operate within dynamic and complex environments …