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 …

Robot learning of manipulation skills is hindered by the scarcity of diverse, unbiased
datasets. While curated datasets can help, challenges remain in generalizability and real …

The advent of the sixth generation of mobile communications (6G) ushers in an era of
heightened demand for advanced network intelligence to tackle the challenges of an …

Scaling laws have driven remarkable progress across machine learning domains like
language modeling and computer vision. However, the exploration of scaling laws in …

Companion robots are aimed to mitigate loneliness and social isolation among older adults
by providing social and emotional support in their everyday lives. However, older adults' …

The realization of universal robots is an ultimate goal of researchers. However, a key hurdle
in achieving this goal lies in the robots' ability to manipulate objects in their unstructured …

Legged locomotion holds the premise of universal mobility, a critical capability for many real-
world robotic applications. Both model-based and learning-based approaches have …

The rapid development of generative technology opens up possibility for higher level of
automation, and artificial intelligence (AI) embodiment in robotic systems is imminent …

Computer Science (CS) stands as a testament to the intricacies of human intelligence,
profoundly advancing the development of artificial intelligence and modern society …