Evaluation of an assurance framework for naval electro-optic-based machine learning applications
- Alignment of naval EO assurance with AMLAS to enable trusted ML-based autonomy.
- Progressive assurance tightening across autonomy levels, reflecting the shift from human-in-the-loop to human-on-the-loop and beyond.
- Embedded safety mechanisms: health monitoring, watchdogs, and fault-tolerant operation.
- Application of STPA and SOTIF, to identify hazards from both system malfunctions as well as deployment in unsuitable operating environments, respectively
