docs(perception): record full TGS shadow acceptance
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# M4.9T5 full source-paced TRAVEL TGS shadow — 2026-08-26
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Status: **recorded source-paced CPU shadow accepted; candidate retained**.
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Visual traversability quality, full-graph performance, navigation and actuation
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remain unaccepted.
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## Decision
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The gravity-aligned TGS-only candidate completed the entire `RAVNOVES00`
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recorded timeline on Worker 006. Every source timeline frame and every eligible
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LiDAR point is represented. No frame was dropped for capacity, AOS was never
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invoked, no GPU was requested and the canonical Triton container remained
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healthy with the same identity.
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This accepts TGS as a bounded CPU shadow candidate. It does not yet make TGS a
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navigation authority or prove that its occupied/ground interpretation is
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correct for vegetation, terrain, gaps or the future vehicle envelope.
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## Frozen identity
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| Item | Identity |
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| --- | --- |
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| LAB result | `m49-tgs-full-shadow-0faeaaf3aba8dccae974eab51ff9cccf264a13ec285abb1920c1e5a09a7e87bc` |
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| Worker run | `Worker 006 / ravnoves00-full-001` |
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| Mission Core revision used by Worker | `40c850b167dda366d8aa45d828520168affaf9fd` |
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| Deterministic Worker artifact | `5e0ea16c7a5cc760463836718b0cd8b0006ffc4b202e5f706a20a86ef2f912ab` |
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| Source pack SHA-256 | `0685d24219d8236caf8b7f1685e93f6d6b59e7fd015a768d88a92bbe8b154944` |
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| TGS config SHA-256 | `c2e07010aaee78259d36c057962d6bfb885349251ff7356d867e5813e632881c` |
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| Linked visual result | `m4-threat-replay-2a953c5f27f2a5b1dddc5c658c1de2c323d7796084a099c024987a1da03aa324` |
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The profile is a `0.45 m`, `12 m` radius, `1 s` causal rolling
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`map-gravity-local` costmap. The four states remain separate:
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`GROUND_SUPPORT`, `NONGROUND_OCCUPIED`, `UNKNOWN_REJECTED` and `UNOBSERVED`.
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## Full-run result
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| Measurement | Result |
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| --- | ---: |
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| Timeline | `4,489 / 4,489` frames |
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| LiDAR available / missing | `3,928 / 561` |
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| Recorded duration / effective rate | `448.623 s / 10.003945 FPS` |
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| Eligible points | `63,646,163` |
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| Ground / non-ground / rejected | `16,579,467 / 47,046,815 / 19,881` |
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| Unaccounted points | `0` |
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| TGS p50 / p95 / p99 / max | `1.190 / 1.694 / 2.08973 / 9.106 ms` |
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| Completion age p50 / p95 / p99 / max | `17.920792 / 29.140775 / 41.428455 / 659.980295 ms` |
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| Capacity drops | `0` |
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| Worker wrapper wall time | `569.401084 s` |
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All formal source-paced, point-accounting and capacity gates passed. The
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completion-age maximum is retained as an outlier; the accepted gate is the
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measured `p99 = 41.43 ms`, not the maximum.
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## Fail-closed behavior
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The `561` timeline frames without a LiDAR sample are not removed, interpolated
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or copied from the preceding frame. Each is emitted as a complete `2,244`-cell
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costmap with all states explicitly `UNOBSERVED`, zero occupied cells and zero
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source points. This preserves chronology without inventing free space.
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## Canonical LAB publication and UI acceptance
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The immutable result is published on the canonical Mission Core service at
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port `8000`. The LAB reuses the recorded camera timeline and exposes independent
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`SOURCE POINTS`, `TGS COSTMAP`, `3D` and `PLAN` controls.
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The first implementation fetched one large JSON frame at a time. Browser QA
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showed that this was only intermittently exact at `1×`. The published viewer
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therefore uses immutable chunks of `24` spatial frames and prefetches the next
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chunk. A final `1×` browser acceptance sampled twenty consecutive positions
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across chunk boundaries: all twenty displayed the exact TGS frame and none
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showed the loading placeholder. A real missing-LiDAR frame was separately
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accepted with `0 source points`, `2,244 unobserved`, `0 occupied` and no retained
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previous cloud.
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## Sealed evidence
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| File | Bytes | SHA-256 |
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| --- | ---: | --- |
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| `costmap-states.npy` | `10,073,444` | `4173f8b6b743755d6d6cbd863c433fe44853974bdd4898002e08574a65783a1a` |
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| `costmap-z-bounds-m.npy` | `80,586,656` | `f8d68b5ca09860ef857a22e15e114bbeabde32492d5c821ee59dfa62ae40373a` |
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| `frames.ndjson` | `1,178,262` | `878e20806d55cdc1fa16692397e11a0e56af760a83c173c8fc73319a39b0e779` |
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| `worker-summary.json` | `1,076` | `487d4be6f3d724bca647aa2e48ba89e7ffd0c78f1bfc5e7e5a01e1db82379dc7` |
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## Next gate
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Attach this unchanged TGS stage to the realtime world-state graph in shadow
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mode alongside the frozen camera semantic-risk provider. Measure complete-graph
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FPS, end-to-end latency, CPU/GPU/VRAM and queue drops against the accepted
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baseline. Keep navigation authority off. In parallel, review the full camera +
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source cloud + TGS timeline for false occupied carpets, missed compact
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obstacles, vegetation and usable gaps. Only the combination of acceptable
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visual behavior and acceptable integrated-graph regression can promote the
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candidate beyond shadow.
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