# Autonomous systems

Robots and vehicles get model updates in the field, often from a supplier.

> **Intended, not deployed.** Intended application areas. Vraelis has no customer deployments in them.

## Models ship to machines in the field.

### Updates land in someone else's fleet

In a facility or fleet the supplier does not operate.

### An unexpected release is a security and operational risk

A different release, or the wrong machine, changes what it does.

### The first question is which model

When a machine surprises you, the answer should come from a record.

> **Hypothesis.** Robotics is one segment we study. Release and platform engineers at robotics suppliers and integrators meet this problem early.

## The workflow, in this area

1. Identify the release.
2. Bind approval to the release and destination. Destination-bound approval: one machine's approval does not cover another.
3. Integrate with a supported runtime.
4. Compare approved and reported. A version mismatch shows as reload pending, not assumed.
5. Preserve discrepancies, missing evidence and recovery.

![Approved cpu-2 beside reported loaded cpu-1, with the differing fields marked.](https://vraelis.com/v8/contour/crop-pair-pending.webp)

*Read-only evidence app, inside the controlled ONNX reference experiment.*

## Not claimed

- No deployments on robots or vehicles, and no customers.
- No robot or vehicle integration. The experiment is a synthetic ONNX CPU workload.
- No protection against adversarial inputs or perception attacks.
- No certification, and no evidence freshness for machines in the field: heartbeats are not built.
- No hardware attestation. Runtime identity is a worker self-report.

- [Autonomous systems on vraelis.com](https://vraelis.com/applications/autonomous-systems): The page this summary comes from.
- [Model integrity](https://docs.vraelis.com/model-integrity): Related research.
- [Adversarial threats](https://docs.vraelis.com/adversarial-threats): Related research.
- [Security evidence](https://docs.vraelis.com/security-evidence): Related research.

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Vraelis documentation, Vraelis. https://docs.vraelis.com/autonomous-systems