Autonomy Test and Evaluation/ T&E

Definition

Autonomy Test and Evaluation is test discipline for validating autonomous systems across simulation, hardware, field trials, and adversarial scenarios. In defense applications, it builds evidence that autonomy works under expected and degraded mission conditions. The hard part is scenario sparsity and sim-to-real gaps, especially when systems are deployed across contested links, coalition boundaries, and mixed human-machine teams. KhanBMS treats it as the evidence pipeline behind KhanBMS deployment decisions, tying the concept back to modular command, edge execution, and auditable authority.

Reference attributes

Layer

verification discipline

Operational value

Builds evidence that autonomy works under expected and degraded mission conditions

Primary risk

Scenario sparsity and sim-to-real gaps

KhanBMS role

The evidence pipeline behind KhanBMS deployment decisions

Related terms

• Digital Twin Simulation
  Live or synchronized synthetic replica of a platform, unit, network, or environment used for testing and rehearsal.
• Simulation-to-Real AI (Sim2Real)
  Techniques that transfer AI behavior trained in simulation into physical platforms and real operations.
• AI Red Teaming
  Structured adversarial testing of AI systems to expose unsafe, biased, exploitable, or brittle behavior.
• Run-Time Assurance for AI (RTA-AI)
  Safety architecture that monitors AI outputs and switches to a verified fallback when behavior leaves bounds.