ruvnet / ruvnet/RuVector

[PIR][WP14] Validate ruvector-perception (3.8K LOC) against real CSI captures, not synthetic-only

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pir stretch
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Rust
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Description

Epic: #837 · Cross-repo counterpart: ruvnet/RuView#1657 · Plan: docs/research/perpetual-intelligence-runtime/03-program-plan.md

Goal

crates/ruvector-perception is 3.8K LOC and has only ever been validated against synthetic data. Validate it against real CSI captures, and establish a documented accuracy baseline.

This is the ruvector-side companion to RuView's WP14 (ruvnet/RuView#1657), which closes ADR-178's gaps C (CSI I/Q → pose-semantics) and D (mcp-brain-server-side cluster consumer).

Why it matters to the program

PIR's invariant 6 is "every physical action produces new evidence," and the 30-day acceptance harness (WP12) logs sensing accuracy as one of its four metric families. A perception stack validated only on synthetic data cannot support that metric — the harness would be measuring agreement with a simulator, not with the world.

The ruview-csi-bridge at crates/ruvector-hailo-cluster/src/bin/ruview-csi-bridge.rs is currently transport-only: it parses RuView's ADR-018 UDP CSI frames and posts a header-summary string into the Hailo embed RPC, with a source comment explicitly disclaiming pose embedding. crates/ruvector-mmwave (Seeed MR60BHA2/LD2410 radar, ADR-063) provides a ground-truth comparison channel.

Acceptance criteria

  • A documented accuracy baseline for ruvector-perception on real CSI captures, reported separately from its synthetic-data performance so any gap between the two is visible rather than averaged away.
  • A real-capture dataset exists and is reproducible — capture conditions, hardware, and chipset recorded, since chipset dependence is the open research question RuView's WP14 addresses.
  • Where mmWave/radar ground truth is available, perception output is compared against it and the discrepancy characterized.
  • If real-capture accuracy falls materially below synthetic, that is reported as the finding, not treated as a blocker to be tuned away. Knowing the synthetic-to-real gap is the point of this work package.
  • The measured baseline is wired into WP12's sensing-accuracy metric if WP14 lands within the acceptance window.

Dependencies

None on the critical path — independent, recommended for separate funding alongside ruvnet/RuView#1657, which supplies the pose-semantic pipeline this validates against.

Contributor guide

No contributing guide indexed for this repository

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Start by reading docs/research/perpetual-intelligence-runtime/03-program-plan.md and the crates/ruvector-perception scope. Inspect crates/ruvector-hailo-cluster/src/bin/ruview-csi-bridge.rs and the synthetic validation before planning real CSI captures and the mmWave comparison. Done means a reproducible dataset, separate real-versus-synthetic accuracy baseline, discrepancy report, and WP12 integration if applicable.

Written by the indexing model from the issue text.

Assessment

Tech stack
rust
Domain
ai, embedded-iot, testing-qa
Issue type
Feature
Difficulty
5/5
Estimated time
Over a week
Activity status
Quiet
Clarity
Mostly clear
Newbie friendliness
35/100

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