Robonaut2 (R2) is a humanoid robot onboard the International Space Station (ISS), performing specialized tasks in collaboration with astronauts. After deployment, R2 developed an unexpected emergent behavior. R2’s inability to distinguish between knee-joint faults (e.g., due to sensor drift versus violated environmental assumptions) began triggering safety-preserving freezes-in-place in the confined space of the ISS, preventing further motion until a ground-control operator determines the root-cause and initiates proper corrective action. Runtime verification (RV) algorithms can efficiently disambiguate the temporal signatures of different faults in real-time. However, no previous RV engine can operate within the limited available resources and specialized platform constraints of R2’s hardware architecture. An attempt to deploy the only runtime verification engine designed for embedded flight systems, R2U2, failed due to resource constraints. We present a significant redesign of the core R2U2 algorithms to adapt to severe resource and certification constraints and prove their correctness. We further define an optimization enabled by our new algorithms and implement the new version of R2U2. We encode specifications describing real-life faults occurring onboard Robonaut2 using Mission-time Linear Temporal Logic (MLTL) and detail our process of specification debugging, validation, and refinement. We deployed this new version of R2U2 on Robonaut2, demonstrating successful real-time fault disambiguation and mitigation triggering of R2’s knee-joint faults without false positives.