OSTVAL stands for Observe · Structure · Think · Validate · Act · Learn. It is the six-stage operating loop that turns sensor pixels into validated, auditable action — and the formal kernel inside every VAOS deployment.
VAOS is an OSTVAL runtime. OSTVAL is the cognitive operating loop of VAOS. Every camera, robot, or edge agent built on VAOS runs the same six-step closed loop — locally, deterministically, and under a validation envelope before any action is taken.
Each stage produces a formal artifact that feeds the next. The loop is local, sensor-aware, and validation-gated.
Acquire raw signal — frames, depth, audio, IMU, time. VAOS knows what each sensor is and how reliable it is right now.
Pixels become a queryable scene — objects, regions, events, sensor reliability scores. Pure perception ends here.
Reason over the scene against persistent memory and site context. SceneLM / agent policies run in this stage.
Score confidence from sensor reliability, scene quality, memory consistency, and human policy. Action only if validation passes.
Emit gated commands — robot moves, API calls, dashboard alerts, MQTT events. Every act carries its validation envelope.
Record outcomes into local persistent memory. Sites learn themselves; the next loop is informed by every previous one.
A small, audit-ready model. Six verbs, five symbols, one closed loop.
The structured scene state St and the environment context Et at time t, derived from sensors with explicit reliability scoring.
Reasoning Rt is a function of the scene, persistent memory Mt, and temporal context Tt. SceneLM and agent policies live here.
Action confidence is a weighted sum — sensor reliability Cs, memory consistency Cm, temporal stability Ct, human policy fit Ch. The validation envelope of VAOS.
An action At is emitted by policy π only if the validation score crosses threshold τ. Below threshold, the loop yields a no-op + diagnostic.
The next state is a function of current scene, environment, memory, and the validated outcome Vt. Persistent local learning, no cloud round-trip required.
Drift De is the magnitude of difference between observed environment Eo and historical baseline Eh — surface anomalies, recalibrations, or regime shifts.
OSTVAL is a stated model. Every stage has an input, an output, and a confidence — so every decision can be replayed, traced, and verified.
Nothing leaves the runtime without crossing the validation threshold. Robots, dashboards, and APIs only see actions that passed the envelope.
Sites accumulate context over time. The same camera at the same site becomes more accurate week after week — without sending data to a cloud.
Five lines of Python. Any RK3588, Jetson, or x86 box. Local cognition with a validation envelope.