  This paper presents a framework that enables robots to automatically recover
from assumption violations of high-level specifications during task execution.
In contrast to previous methods relying on user intervention to impose
additional assumptions for failure recovery, our approach leverages
synthesis-based repair to suggest new robot skills that, when implemented,
repair the task. Our approach detects violations of environment safety
assumptions during the task execution, relaxes the assumptions to admit
observed environment behaviors, and acquires new robot skills for task
completion. We demonstrate our approach with a Hello Robot Stretch in a
factory-like scenario.
