Robot-Initiated Specification Repair through Grounded Language Interaction
This addresses the disconnect between user intent and robot representation for robotics applications, though it appears incremental as it builds on existing grounding and synthesis methods.
The paper tackles the problem of robots executing complex instructions in dynamic environments by introducing a framework that uses formal synthesis to identify necessary environment assumptions and prompts users to confirm or reject them via natural language questions, demonstrated on tabletop pick-and-place tasks.
Robots are required to execute increasingly complex instructions in dynamic environments, which can lead to a disconnect between the user's intent and the robot's representation of the instructions. In this paper we present a natural language instruction grounding framework which uses formal synthesis to enable the robot to identify necessary environment assumptions for the task to be successful. These assumptions are then expressed via natural language questions referencing objects in the environment. The user is prompted to confirm or reject the assumption. We demonstrate our approach on two tabletop pick-and-place tasks.