# Roboarm VLA

![Roboarm manipulation](/files/tP91L9z3cuDOOITRCkeG)

**Workload class:** text-directed **vision–language–action (VLA)** manipulation — bi-manual and kitchen-grade scenarios are common examples; the subnet is not limited to food service.

On testnet, operators issue **task prompts**; miners compete on **trajectories and policies** from VLA / control stacks; validators score candidates on **safety**, **task match**, and **efficiency**. Outputs feed [Proof-of-Physical-Work (PoPW)](/understand-konnex/contracts-and-popw.md) records on the Konnex testnet.

## Testnet

The public dashboard URL for this workload will be announced with the testnet release.

## Task shape (illustrative)

The live UI and chain define the exact fields. Example natural-language tasks:

* *"Pick the apple from the pan and place it on the counter."*
* *"Dice tomatoes and place them into the pan."*

A JSON sketch:

```json
{
  "jobId": "sha3(signed-packet)",
  "prompt": "dice tomatoes and place into pan",
  "arena": "KitchenSim-v1",
  "deadline": 120,
  "rewardTestKNX": "…",
  "kpi": {"time_s": 90, "success": true, "spills": 0}
}
```

Use the fields and token type shown in the testnet product (e.g. testKNX).

## Miner output

* Policy or VLA bundle (e.g. WASM or integration endpoint) with deterministic seeds where the subnet requires them
* Declared KPIs and stake per network rules

## Validation flow (conceptual)

1. Deterministic replay in the subnet’s simulator or harness when applicable.
2. KPI extraction and safety checks.
3. ScoreRoot emission; rewards or slashing per onchain parameters.

## Example prompt

"Pick the red bell pepper, slice into strips, sauté for 2 minutes, then place on the plate."

## See also

* [Subnets overview](/subnets-workload-classes/subnets.md)
* [OpenVLA](/supported-ai-models/openvla.md) · [PI-0 / PI-0.5](/supported-ai-models/ai.md)
* [Decentralized AI ecosystem](/understand-konnex/ai-ecosystem.md)


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.konnex.world/subnets-workload-classes/roboarm-vla.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.