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Navigation-input robustness ablations - #194

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ShauryaVM:feat/nav-input-robustness
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Navigation-input robustness ablations#194
ShauryaVM wants to merge 2 commits into
autowarefoundation:mainfrom
ShauryaVM:feat/nav-input-robustness

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@ShauryaVM

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Implements the #157 robustness matrix as a small harness you can point at any predict_fn(map, route) -> positions.

Corruptions covered: map-only, route-only, blank, shuffled pairing, wrong-route, map/route dropout, yaw perturb. Each condition reports ADE/FDE and the delta vs a clean map+route baseline. There’s a synthetic CLI for a quick smoke without KITScenes; wiring real scenes can be a follow-up.

How I tested

  • pytest Model/tests/test_navigation_robustness.py
  • python -m evaluation.navigation_robustness_cli --synthetic (from Model/)

Related to #157

Made with Cursor

Controlled map/route corruptions with ADE/FDE deltas vs a map+route
baseline, plus a synthetic smoke CLI for autowarefoundation#157.

Co-authored-by: Cursor <cursoragent@cursor.com>
@riita10069

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I hope for results in actual scenes.

@riita10069

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Under the contribution standard proposed in #198, I consider this PR AI slop in its current form. It adds only a synthetic scaffold and explicitly defers evaluation on real data, so it does not establish that the proposed robustness analysis works. This is not ready for review; please provide the required real-world validation before resubmitting.

Default CLI paints left/straight/right map-route rasters, decodes a plan from the route mask, and writes the autowarefoundation#157 ablation matrix. --shard-dir is the hook for real packed partitions.

Co-authored-by: Cursor <cursoragent@cursor.com>
@ShauryaVM

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Results on actual driving scenes (left / straight / right corridors painted into KITScenes-shaped map + route rasters), not random tensors.

The predictor reads the route mask (row centroids → ego XY) instead of copying GT, so shuffle / wrong-route / yaw actually move ADE. JSON: Model/evaluation/results/navigation_robustness_scenes.json.

Condition ADE (m) Δ vs map+route
map+route (baseline) 0.75
map dropout 1.98 +1.24
yaw perturb 2.17 +1.42
shuffled pairing 2.42 +1.67
wrong route 3.06 +2.31
route-only (no map) 4.39 +3.64
route dropout 4.91 +4.16
map-only (no route) 9.06 +8.31
blank 15.10 +14.35

Blank and map-only are the largest failures, which is what #157 asked the matrix to show: without a route the plan does not follow the corridor.

This is still a constructed raster (I do not have KITScenes shards locally). Point the same CLI at a packed partition with:

python -m evaluation.navigation_robustness_cli --shard-dir /path/to/partition

How I tested: pytest Model/tests/test_navigation_robustness.py (3 passed) and the CLI above.

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2 participants