Challenges in Grounding Language in the Real World
This addresses the problem of grounding language in real-world robotics for AI researchers, but it is incremental as it builds on existing methods without introducing a new paradigm.
The paper tackles the challenge of enabling natural language collaboration between humans and physical robots by integrating a cognitive agent for interactive task learning with a large language model, and outlines an initial implementation approach.
A long-term goal of Artificial Intelligence is to build a language understanding system that allows a human to collaborate with a physical robot using language that is natural to the human. In this paper we highlight some of the challenges in doing this, and propose a solution that integrates the abilities of a cognitive agent capable of interactive task learning in a physical robot with the linguistic abilities of a large language model. We also point the way to an initial implementation of this approach.