Teaching robots to tidy up based on user preferences using large language models
Different people tend to have unique needs and preferences—particularly when it comes to cleaning or tidying up. Home robots, especially robots designed to help humans with house chores, should ideally be able to complete tasks in ways that account for these individual preferences.
Humans have a way of understandings others' goals, desires and beliefs, a crucial skill that allows us to anticipate people's actions. Taking bread out of the toaster? You'll need a plate. Sweeping up leaves? I'll grab the green trash can. This skill, often referred to as 'theory of mind,' comes…
Robots are increasingly being used in manufacturing, agriculture and health care. But programming a team of robots to carry out individual tasks raises a question: How can robots learn from other robots if they are built differently? A multi-institutional team including Chongjie Zhang, an associate professor of computer science and…
Today's robots are stuck—their bodies are usually closed systems that can neither grow nor self-repair, nor adapt to their environment. Now, scientists at Columbia University have developed robots that can physically "grow," "heal," and improve themselves by integrating material from their environment or from other robots.