By structuring robot learning around explicit skill hierarchies with clear input-output contracts and execution-grounded diagnosis, robots can reliably improve their capabilities through experience and safely reuse learned skills across new tasks.
RoboRSI is a robot self-improvement system that learns and refines skills through real-world experience. It organizes task execution into a hierarchy of skills (compound, atomic, base) with clear responsibilities, diagnoses failures to pinpoint which skill needs fixing, and validates improvements before reusing them.