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build(deps): bump actions/upload-pages-artifact from 4 to 5#2

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build(deps): bump actions/upload-pages-artifact from 4 to 5#2
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dependabot/github_actions/actions/upload-pages-artifact-5

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@dependabot dependabot Bot commented on behalf of github May 17, 2026

Bumps actions/upload-pages-artifact from 4 to 5.

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v5.0.0

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Bumps [actions/upload-pages-artifact](https://github.com/actions/upload-pages-artifact) from 4 to 5.
- [Release notes](https://github.com/actions/upload-pages-artifact/releases)
- [Commits](actions/upload-pages-artifact@v4...v5)

---
updated-dependencies:
- dependency-name: actions/upload-pages-artifact
  dependency-version: '5'
  dependency-type: direct:production
  update-type: version-update:semver-major
...

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dependabot Bot commented on behalf of github May 17, 2026

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@dependabot dependabot Bot requested a review from NMGorovenko as a code owner May 17, 2026 16:55
NMGorovenko added a commit that referenced this pull request May 25, 2026
Two changes that together eliminate the bang-bang behaviour that BC
was learning as noise:

1. **Corner-only targets.** curated_paths.control_points() returns
   just the direction-change cells of a path (plus start and goal)
   instead of every grid cell. The auto-pilot drives toward sparse
   corners rather than retargeting every 45 cm.

2. **ALIGN / DRIVE phase machine.** In drive_episode:
   * ALIGN: rotate (DirLeft/DirRight) until heading is within ±6°
     of the line-to-target. Single sustained rotation, no
     bang-bang.
   * DRIVE: pure DirForward until the corner is reached. The only
     mid-segment correction is a hard fallback when heading has
     drifted past ±18° (rare — the corridor walls themselves
     mostly rail the robot).
   * On reach-distance hit OR overshoot (current distance > 1.5×
     the minimum seen this segment), reset to ALIGN for the next
     corner.

The BC student now sees long sequences of DirForward labels on
identical "corridor-straight-ahead" frames, then a short cluster
of DirLeft/DirRight at each corner, then more Forwards. That's the
"align — drive — align — drive" pattern a human operator produces.
The previous controller, even with hysteresis, kept micro-correcting
through every segment because the heading error grew asymptotically
as the robot approached each per-cell target.

Re-recorded the 10 curated maze demos:
  * All 10 still reached_goal (87-166 steps vs 210-296 previously
    — shorter because cleaner trajectory)
  * Total samples 1204 (was 2603; fewer steps × same FPS)
  * Action mix Forward 57.8 % / Left 17.9 % / Right 24.3 %
    (was 30.5 / 33.0 / 36.4 — F nearly doubled)
  * Simple L paths (#1, #2): 71-77 % Forward
  * 4-corner stairs (#7, #8): 50 % Forward
  * Distribution now scales with corner density, as expected
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