Commit Graph

4 Commits

Author SHA1 Message Date
Johnny Fernandes 7ab69ab0f3 Rename multi-segment functions to two-concept names; polish docstrings
Naming pass: rename functions whose third+ segment is redundant or
implementation-detail, sticking to the codebase's preferred
``noun_verb`` / ``verb_noun`` two-concept idiom. Renames are atomic
across definitions, callers, and tests.

  is_penned_position        →  is_penned
  modulate_speed_near_sheep →  modulate_speed
  mecanum_kinematics_step   →  mecanum_step
  policy_forward_mean       →  forward_mean

Two-concept patterns like ``velocity_to_wheels`` / ``detections_from_scan``
/ ``make_strombom_predictor`` are left alone — they're idiomatic
converters / factories that read as a single concept, and the longer
form aids grep-ability.

Docstring polish:
* ``herding/config.py`` header drops the "previously lived as a
  module-level literal" historical framing — we ship as a single
  thing, so the refactor anecdote no longer earns its keep. The
  usage examples now mention both ``HERDING_WEBOTS`` and
  ``HERDING_MEC_WEBOTS`` presets.

126 pytest cases still pass.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
2026-05-17 01:58:15 +00:00
Johnny Fernandes 2d23289052 Consensus tracker + active scan close Webots 140° LiDAR gap
Two deploy-time fixes that take v1 360°-trained BC/RL from 0/n to n/n
penned on the canonical 140° LiDAR proto for diff/field:

* SheepTracker now supports a consensus stage: new detections start as
  candidate tracks invisible to get_positions(). A candidate must
  accumulate consensus_k matches within consensus_radius_m of itself
  inside a consensus_max_age window to be promoted; otherwise it
  expires. Real sheep self-confirm within 3 frames (≪0.05 m/step);
  wall-return cluster centroids jitter beyond 0.3 m as the dog moves
  and never promote. consensus_k=1 (default) is a no-op so unconfigured
  callers and HERDING_DEFAULT keep prior behaviour.
* HERDING_WEBOTS preset gets consensus_k=3, radius=0.3, max_age=20,
  plus longer forget_steps=300 and predict_steps=180 so confirmed
  sheep persist through long FOV-occlusion gaps a narrow 140° cone
  produces. max_new_tracks_per_step=1 still rate-caps spawn bursts.
* shepherd_dog.py BC/RL empty-obs fallback now rotates the desired
  heading with step_count so the cone actively sweeps the field
  instead of driving due north into the wall.

Verified in headless Webots (HERDING_USE_GT=0, LiDAR only):
  BC diff/field:        5/5 @ 11698, 10/10 @ 15079
  RL diff/field:        5/5 @ 10039, 9/10 @ 18200 (timeout)
  Strömbom diff/field:  5/5 @ 7528
All previously 0/n. 120 unit tests pass; 9 new consensus tests cover
the candidate stage, promotion radius, and one-shot phantom rejection.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
2026-05-16 20:19:11 +00:00
Johnny Fernandes 5c2ee4bba5 Checkpoint 8 2026-05-12 22:41:03 +01:00
Johnny Fernandes a01a5c9cef Checkpoint 7 2026-05-11 12:21:51 +01:00