Commit Graph

29 Commits

Author SHA1 Message Date
Dom 487dfc4bf4 FLM: preserve fresh evidence across paired queue drains
Merge bounded control/output FIFO heads using original publisher headers. Preserve original age, native, source, overflow and malformed-input checks; retain producer order after joins.

Validated with actual pinned cloud dependencies and fresh-head regression tests.
2026-10-27 17:01:24 -05:00
firestar5683 6103e0395b Preserve FLM learning windows across unchanged steering repeats
The d5 Ioniq 6 logs repeatedly reset source tracking when Card repeats a command that already arrived on time. Discard only a recent unchanged repeat after the existing native CAN verifier succeeds; add no sample, application time or permission.

Use independently admitted pending CarState brackets to complete original poses without waiting for that command to reach Card. Classify stale control source clocks as transient stale evidence, preserving the original bounded study deadline. Replace Python character loops with equivalent strict text predicates.

Validation: focused regression suite and paced d5 replay with original Card command references; actual controller/CAN trial application and worsening-trial rollback. No timing/acceptance threshold changes or claimed road improvement.
2026-10-26 21:55:26 -05:00
firestar5683 ec25e2330a Consume pending native evidence before FLM collection 2026-10-26 11:41:40 -05:00
firestar5683 0f00621c98 Coalesce refreshed FLM receipts with scheduled tracking 2026-10-26 09:34:09 -05:00
firestar5683 0e5e5574c4 Publish refreshed FLM collection receipts on tracking 2026-10-26 09:09:55 -05:00
firestar5683 f3bbd38e81 Wake Auto Learn on fresh motion and native evidence 2026-10-25 21:05:53 -05:00
firestar5683 3c740d2050 Allow conflated car state snapshots in Auto Learn 2026-10-25 13:55:50 -05:00
firestar5683 4c250a6a06 Restore Auto Learn source admission after GPU startup fix 2026-10-24 21:55:54 -05:00
firestar5683 24126eafdc Keep source learning progressing after interrupted trials 2026-10-24 09:45:44 -05:00
firestar5683 d2f3acc248 Keep calibrated configuration across learner receipt gaps 2026-10-23 20:10:59 -05:00
firestar5683 0022fde1cb Fix Auto Learn collection recovery after evidence gaps 2026-10-23 17:36:10 -05:00
firestar5683 a5eda8a63a Fix Auto Learn authorization and tracking delivery timing 2026-10-23 17:13:21 -05:00
firestar5683 cdb7e7a5d4 Reject missing Auto Learn withdrawal receipts 2026-10-22 21:39:39 -05:00
firestar5683 95155234e8 Publish explicit Auto Learn source withdrawals 2026-10-22 21:37:28 -05:00
firestar5683 15a78b9b33 Maintain Auto Learn source delivery cadence 2026-10-22 21:29:34 -05:00
firestar5683 ca2373a9a0 Refresh Auto Learn inputs after queued decoding 2026-10-22 20:14:03 -05:00
firestar5683 62dc081f70 Keep Auto Learn source publication responsive 2026-10-22 19:10:12 -05:00
firestar5683 1f66903899 Recover Auto Learn after calibration delivery gaps 2026-10-22 11:11:11 -05:00
firestar5683 b151ca11cb Global FLM Auto Learn 2026-10-21 23:28:39 -05:00
firestar5683 3a8dbe75f1 Repair CI Contracts 2026-10-19 00:47:35 -05:00
firestar5683 6ce281bf5f Fix FLM evidence and proposal lifecycle 2026-10-18 18:30:31 -05:00
firestar5683 07adfe819e Complete FLM learning pipeline 2026-10-17 23:26:55 -05:00
firestar5683 5b12042b88 Fix lateral learning intake 2026-10-17 20:02:38 -05:00
firestar5683 2cd7728be2 FLM Auto-Weave 2026-10-17 18:38:27 -05:00
firestar5683 198a9fca63 FLM Training Results 2026-10-17 10:53:16 -05:00
firestar5683 53309097e9 Fix Auto Learn collection renewal 2026-10-16 17:21:48 -05:00
firestar5683 abb9646499 FLM Calibration Lifecycle
Keep bounded automatic learning collection through valid live calibration refinements. Retire generations on resets or invalid calibration, preserve live physical transforms and existing controller tunes, and validate fitted coefficient bounds before publication. Exercise the current controller and historical wire paths.
2026-10-16 09:47:39 -05:00
firestar5683 7e63c553a4 FLM Auto-Weave 2026-10-16 08:46:39 -05:00
firestar5683 200632aabd StarPilot Auto Learn
Learn bounded feed-forward corrections on eligible torque controllers behind Use StarPilot Auto Learn, preserving installed tunes and native safety limits.
Co-authored-by: Danny <dannyirwin31@yahoo.com>
Co-authored-by: Dom <168790843+firestar5683@users.noreply.github.com>
Co-authored-by: Harald Schäfer <harald.the.engineer@gmail.com>
Co-authored-by: Prabhaav Pillai <prabhaav@msu.edu>
Co-authored-by: dirwin31 <83434411+dirwin31@users.noreply.github.com>
Co-authored-by: firestarsdog <229254897+firestarsdog@users.noreply.github.com>

Co-authored-by: Intelli <contact@intelli.software>
Co-authored-by: haraschax <6804392+haraschax@users.noreply.github.com>
Co-authored-by: pharmacomaniac <blittle65@gmail.com>

Co-authored-by: whoisdomi <dcantu83@gmail.com>
2026-10-14 20:02:39 -05:00