Transfer learning in robotics: From promises to practice through the emerging role of foundation models.

Key Points

• The aim is to explore how foundation models can facilitate transfer learning in robotics across different tasks and environments.
• Analysis of foundation models in robotics applications
• Assessment of their effectiveness across multiple tasks and environments
• Foundation models significantly improve transfer learning capabilities across varied robotic contexts.
• Facilitated transfers show promise in enhancing adaptability in unforeseen robotic tasks.

Abstract